{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 在Pima Indians Diabetes Data Set（皮马印第安人糖尿病数据集）进行分类器练习。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1  导入工具包"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jack/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n",
      "  return f(*args, **kwds)\n",
      "/home/jack/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n",
      "  return f(*args, **kwds)\n",
      "/home/jack/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n",
      "  return f(*args, **kwds)\n",
      "/home/jack/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n",
      "  return f(*args, **kwds)\n",
      "/home/jack/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n",
      "  return f(*args, **kwds)\n",
      "/home/jack/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n",
      "  return f(*args, **kwds)\n",
      "/home/jack/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n",
      "  return f(*args, **kwds)\n"
     ]
    }
   ],
   "source": [
    "# import必要的模块\n",
    "import pandas as pd \n",
    "import numpy as np\n",
    "\n",
    "from sklearn.linear_model import LogisticRegression  \n",
    "from sklearn.model_selection import GridSearchCV  \n",
    "from sklearn.metrics import classification_report \n",
    "\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "#竞赛的评价指标为logloss\n",
    "from sklearn.metrics import log_loss  \n",
    "from sklearn import metrics\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2 读取数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pregnancies</th>\n",
       "      <th>Glucose</th>\n",
       "      <th>BloodPressure</th>\n",
       "      <th>SkinThickness</th>\n",
       "      <th>Insulin</th>\n",
       "      <th>BMI</th>\n",
       "      <th>DiabetesPedigreeFunction</th>\n",
       "      <th>Age</th>\n",
       "      <th>Outcome</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6</td>\n",
       "      <td>148</td>\n",
       "      <td>72</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>33.6</td>\n",
       "      <td>0.627</td>\n",
       "      <td>50</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>85</td>\n",
       "      <td>66</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>26.6</td>\n",
       "      <td>0.351</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "      <td>183</td>\n",
       "      <td>64</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23.3</td>\n",
       "      <td>0.672</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>89</td>\n",
       "      <td>66</td>\n",
       "      <td>23</td>\n",
       "      <td>94</td>\n",
       "      <td>28.1</td>\n",
       "      <td>0.167</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>137</td>\n",
       "      <td>40</td>\n",
       "      <td>35</td>\n",
       "      <td>168</td>\n",
       "      <td>43.1</td>\n",
       "      <td>2.288</td>\n",
       "      <td>33</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Pregnancies  Glucose  BloodPressure  SkinThickness  Insulin   BMI  \\\n",
       "0            6      148             72             35        0  33.6   \n",
       "1            1       85             66             29        0  26.6   \n",
       "2            8      183             64              0        0  23.3   \n",
       "3            1       89             66             23       94  28.1   \n",
       "4            0      137             40             35      168  43.1   \n",
       "\n",
       "   DiabetesPedigreeFunction  Age  Outcome  \n",
       "0                     0.627   50        1  \n",
       "1                     0.351   31        0  \n",
       "2                     0.672   32        1  \n",
       "3                     0.167   21        0  \n",
       "4                     2.288   33        1  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train = pd.read_csv(\"./data/diabetes.csv\")\n",
    "train.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3 数据分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 768 entries, 0 to 767\n",
      "Data columns (total 9 columns):\n",
      "Pregnancies                 768 non-null int64\n",
      "Glucose                     768 non-null int64\n",
      "BloodPressure               768 non-null int64\n",
      "SkinThickness               768 non-null int64\n",
      "Insulin                     768 non-null int64\n",
      "BMI                         768 non-null float64\n",
      "DiabetesPedigreeFunction    768 non-null float64\n",
      "Age                         768 non-null int64\n",
      "Outcome                     768 non-null int64\n",
      "dtypes: float64(2), int64(7)\n",
      "memory usage: 54.1 KB\n"
     ]
    }
   ],
   "source": [
    "train.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "通过 info 方法可以看到样本数为768个，8个特征值，一个类别判断目标值。 数据中 BMI 和 DiabetesPedigreeFunction 为浮点数，其余数据都为整数。由说明可得 糖尿病家族史应该处理为了一个倍数问题，整体数值都不大。BMI就是我们常见的身高体重的指标，这两个允许浮点数。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pregnancies</th>\n",
       "      <th>Glucose</th>\n",
       "      <th>BloodPressure</th>\n",
       "      <th>SkinThickness</th>\n",
       "      <th>Insulin</th>\n",
       "      <th>BMI</th>\n",
       "      <th>DiabetesPedigreeFunction</th>\n",
       "      <th>Age</th>\n",
       "      <th>Outcome</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>3.845052</td>\n",
       "      <td>120.894531</td>\n",
       "      <td>69.105469</td>\n",
       "      <td>20.536458</td>\n",
       "      <td>79.799479</td>\n",
       "      <td>31.992578</td>\n",
       "      <td>0.471876</td>\n",
       "      <td>33.240885</td>\n",
       "      <td>0.348958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3.369578</td>\n",
       "      <td>31.972618</td>\n",
       "      <td>19.355807</td>\n",
       "      <td>15.952218</td>\n",
       "      <td>115.244002</td>\n",
       "      <td>7.884160</td>\n",
       "      <td>0.331329</td>\n",
       "      <td>11.760232</td>\n",
       "      <td>0.476951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.078000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>62.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>27.300000</td>\n",
       "      <td>0.243750</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>117.000000</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>30.500000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>0.372500</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>6.000000</td>\n",
       "      <td>140.250000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>127.250000</td>\n",
       "      <td>36.600000</td>\n",
       "      <td>0.626250</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>17.000000</td>\n",
       "      <td>199.000000</td>\n",
       "      <td>122.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>846.000000</td>\n",
       "      <td>67.100000</td>\n",
       "      <td>2.420000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Pregnancies     Glucose  BloodPressure  SkinThickness     Insulin  \\\n",
       "count   768.000000  768.000000     768.000000     768.000000  768.000000   \n",
       "mean      3.845052  120.894531      69.105469      20.536458   79.799479   \n",
       "std       3.369578   31.972618      19.355807      15.952218  115.244002   \n",
       "min       0.000000    0.000000       0.000000       0.000000    0.000000   \n",
       "25%       1.000000   99.000000      62.000000       0.000000    0.000000   \n",
       "50%       3.000000  117.000000      72.000000      23.000000   30.500000   \n",
       "75%       6.000000  140.250000      80.000000      32.000000  127.250000   \n",
       "max      17.000000  199.000000     122.000000      99.000000  846.000000   \n",
       "\n",
       "              BMI  DiabetesPedigreeFunction         Age     Outcome  \n",
       "count  768.000000                768.000000  768.000000  768.000000  \n",
       "mean    31.992578                  0.471876   33.240885    0.348958  \n",
       "std      7.884160                  0.331329   11.760232    0.476951  \n",
       "min      0.000000                  0.078000   21.000000    0.000000  \n",
       "25%     27.300000                  0.243750   24.000000    0.000000  \n",
       "50%     32.000000                  0.372500   29.000000    0.000000  \n",
       "75%     36.600000                  0.626250   41.000000    1.000000  \n",
       "max     67.100000                  2.420000   81.000000    1.000000  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## 各属性的统计特性\n",
    "train.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Insulin ,SkinThickness方差较大，波动较大。这可能与缺失值填补0有关系。之后会处理"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4 数据探索"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.1 缺失值处理"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由于本作业把缺失值都编码为0，但是经过观察发现 Insulin,Glucose,BloodPressure,SkinThickness,BMI 这几个值编码为0显然是不正确的，正常人都会有这几个指标。 Pregnancies 未怀孕次数，无法辨别是0值是不是缺失值，不进行处理。\n",
    "我们按是糖药病的人和不是糖药病的人进行分类。按照两个类别分别计算以上几个指标的平均值。然后对这些特征值的缺失值按照平均值进行填补。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jack/anaconda3/lib/python3.6/site-packages/pandas/core/frame.py:3137: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self[k1] = value[k2]\n",
      "/home/jack/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:19: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "/home/jack/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:22: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Pregnancies                 0\n",
       "Glucose                     0\n",
       "BloodPressure               0\n",
       "SkinThickness               0\n",
       "Insulin                     0\n",
       "BMI                         0\n",
       "DiabetesPedigreeFunction    0\n",
       "Age                         0\n",
       "Outcome                     0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 需要进行对0异常值做处理的特征\n",
    "zeroFields = ['Insulin',  'Glucose', 'BloodPressure', 'SkinThickness','BMI']\n",
    "trainFillOne = train[train[\"Outcome\"] == 1]\n",
    "trainFillZero = train[train[\"Outcome\"] == 0]\n",
    "\n",
    "# 建立是不是糖药病的人的两个字典存储平均值\n",
    "zeroDic = {}\n",
    "oneDic = {}\n",
    "for index in zeroFields:\n",
    "     zeroDic[index]=trainFillZero[index].sum()/len(trainFillZero.loc[trainFillZero[index] >0]);\n",
    "     oneDic[index]=trainFillOne[index].sum()/len(trainFillOne.loc[trainFillOne[index] >0]);\n",
    "\n",
    "# 对0值的缺失值进行转换为NA\n",
    "trainFillOne[zeroFields] =trainFillOne[zeroFields].where(trainFillOne[zeroFields]>0)    \n",
    "trainFillZero[zeroFields] = trainFillZero[zeroFields].where(trainFillZero[zeroFields] >0)\n",
    "\n",
    "# 进行填补\n",
    "for key,val in zeroDic.items():\n",
    "    trainFillZero[key]=trainFillZero[key].fillna(val)\n",
    "\n",
    "for key,val in oneDic.items():\n",
    "    trainFillOne[key]=trainFillOne[key].fillna(val)    \n",
    "\n",
    "# 填不完后，把两个dataFrame进行结合，并打乱顺序\n",
    "trainFilled = trainFillZero.append(trainFillOne)\n",
    "trainFilled = trainFilled.sample(frac = 1)\n",
    "trainFilled.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pregnancies</th>\n",
       "      <th>Glucose</th>\n",
       "      <th>BloodPressure</th>\n",
       "      <th>SkinThickness</th>\n",
       "      <th>Insulin</th>\n",
       "      <th>BMI</th>\n",
       "      <th>DiabetesPedigreeFunction</th>\n",
       "      <th>Age</th>\n",
       "      <th>Outcome</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.00000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>3.845052</td>\n",
       "      <td>121.697358</td>\n",
       "      <td>72.428141</td>\n",
       "      <td>29.247042</td>\n",
       "      <td>157.003527</td>\n",
       "      <td>32.44642</td>\n",
       "      <td>0.471876</td>\n",
       "      <td>33.240885</td>\n",
       "      <td>0.348958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3.369578</td>\n",
       "      <td>30.462008</td>\n",
       "      <td>12.106044</td>\n",
       "      <td>8.923908</td>\n",
       "      <td>88.860914</td>\n",
       "      <td>6.87897</td>\n",
       "      <td>0.331329</td>\n",
       "      <td>11.760232</td>\n",
       "      <td>0.476951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>44.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>18.20000</td>\n",
       "      <td>0.078000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>99.750000</td>\n",
       "      <td>64.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>121.500000</td>\n",
       "      <td>27.50000</td>\n",
       "      <td>0.243750</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>117.000000</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>130.287879</td>\n",
       "      <td>32.05000</td>\n",
       "      <td>0.372500</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>6.000000</td>\n",
       "      <td>141.000000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>33.000000</td>\n",
       "      <td>206.846154</td>\n",
       "      <td>36.60000</td>\n",
       "      <td>0.626250</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>17.000000</td>\n",
       "      <td>199.000000</td>\n",
       "      <td>122.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>846.000000</td>\n",
       "      <td>67.10000</td>\n",
       "      <td>2.420000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Pregnancies     Glucose  BloodPressure  SkinThickness     Insulin  \\\n",
       "count   768.000000  768.000000     768.000000     768.000000  768.000000   \n",
       "mean      3.845052  121.697358      72.428141      29.247042  157.003527   \n",
       "std       3.369578   30.462008      12.106044       8.923908   88.860914   \n",
       "min       0.000000   44.000000      24.000000       7.000000   14.000000   \n",
       "25%       1.000000   99.750000      64.000000      25.000000  121.500000   \n",
       "50%       3.000000  117.000000      72.000000      28.000000  130.287879   \n",
       "75%       6.000000  141.000000      80.000000      33.000000  206.846154   \n",
       "max      17.000000  199.000000     122.000000      99.000000  846.000000   \n",
       "\n",
       "             BMI  DiabetesPedigreeFunction         Age     Outcome  \n",
       "count  768.00000                768.000000  768.000000  768.000000  \n",
       "mean    32.44642                  0.471876   33.240885    0.348958  \n",
       "std      6.87897                  0.331329   11.760232    0.476951  \n",
       "min     18.20000                  0.078000   21.000000    0.000000  \n",
       "25%     27.50000                  0.243750   24.000000    0.000000  \n",
       "50%     32.05000                  0.372500   29.000000    0.000000  \n",
       "75%     36.60000                  0.626250   41.000000    1.000000  \n",
       "max     67.10000                  2.420000   81.000000    1.000000  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trainFilled.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.2 定义单变量画直方图和散点图的函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def drawHisAndScatter(dFrame,name):\n",
    "    fig=plt.figure(figsize=(10,5))\n",
    "    sns.distplot(dFrame[name].values, bins=30, kde=True)\n",
    "    plt.title(\"Histogram of \"+name);\n",
    "    plt.xlabel('Value of '+name, fontsize=12)\n",
    "    plt.ylabel('Probability', fontsize=12)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Target 分布，看看各类样本分布是否均衡\n",
    "sns.set()\n",
    "sns.countplot(train.Outcome);\n",
    "plt.xlabel('Outcome');\n",
    "plt.ylabel('Number of occurrences');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由图可以看出，输出是不是糖药病的样本不均衡，不是糖药病的人比是糖药病的人多200多个，在之后的使用模型训练的时候要注意。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.3 单值特征值分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jack/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n",
      "/home/jack/anaconda3/lib/python3.6/site-packages/scipy/stats/stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jack/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jack/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jack/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jack/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jack/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jack/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jack/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for name in trainFilled.columns:\n",
    "    if name != 'Outcome':\n",
    "        drawHisAndScatter(trainFilled,name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "经过处理过后的特征值的分布还不错。 血压BloodPressure 和BMI 基本满足正态分布。Insulin 出现了两个峰值的情况，大概在150和200，可能是与我们填写的平均值有关系。skinThicness也和insulin 一样出现了双峰值，估计也是与我们填补的平均值有关系。这次调研的大部分人数年龄都在20-30岁之间。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jack/anaconda3/lib/python3.6/site-packages/scipy/stats/stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYUAAAEGCAYAAACKB4k+AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAAIABJREFUeJzs3WdglFX69/HvPT2T3kPvTUBQmghSpVdhAdvqqruoz66NXde2lr9dV1lddy2o6+paUEFAROlNpaMCIgIxlCSQRnoy/b6fF0MGohICmZbM9XnjZJjMXEIyvznnPuc6iqZpGkIIIQSgC3UBQgghwoeEghBCCB8JBSGEED4SCkIIIXwkFIQQQvgYQl1AQxQWVoS6BCGEaHRSU2PP+GcyUhBCCOEjoSCEEMJHQkEIIYSPhIIQQggfCQUhhBA+EgpCCCF8JBSEEEL4SCgIIYTwkVAQPtXV1aEuQQgRYhIKAoBVq77gttv+wP79+0JdihAihCQUBACLFy9A0zS+++6bUJcihAghCQUBgKqqAMhBfEJENgkFAUBNFiiKEtpChBAhJaEghBDCR0JBAFAzQJCBghCRTUJB1KKqck1BiEgmoSB+RkJBiEgmoSBqcTqdoS5BCBFCEgoCOLX6yOVyhbYQIURISSiIWlwuGSkIEckkFEQtHo8a6hKEECEkoSCAU0tRa3Y2CxEuVFVlyZKF7N27J9SlRISAhcJ9993HwIEDmThxou++Z555hrFjxzJp0iT++Mc/Ul5e7vuz1157jVGjRjFmzBi+/PLLQJUlzkJ2NItwk5OTzZIlC3n++adCXUpECFgoTJs2jTfeeKPWfYMGDeKzzz5j6dKltG3bltdeew2AzMxMli1bxrJly3jjjTf4v//7PzweT6BKE3WQTBDhxm63hbqEiBKwUOjXrx/x8fG17hs8eDAGgwGA3r17k5eXB8CaNWuYMGECJpOJVq1a0aZNG3bv3h2o0kQd9HpDqEsQohYJheAK2TvAwoULGTduHAD5+fn06tXL92fp6enk5+ef9TkSE60YDPqA1RhJaqaNYmKiSE2NDXE1Qpyi15+6ziU/m4EXklB45ZVX0Ov1TJ48Gfj1ds31mdsuKZGTwvyl5t9AVRUKCytCXI0Qpxw7VnDa7RMYjaYQVtM01BWuQV99tGjRItavX89zzz3ne+PPyMjwTSWBd+SQlpYW7NIE+Kb3hAgX5eVlvttlZWV1PFL4Q1BDYePGjbz++uu88sorREVF+e4fMWIEy5Ytw+l0kp2dzeHDh7nwwguDWVrEqxms6XQyHSfCS3Fxse92SUlxHY8U/hCwj4Vz5sxh27ZtlJSUMGTIEG677TbmzZuH0+nkhhtuAKBXr148+uijdOrUiXHjxjF+/Hj0ej0PPfQQer28OQWTrDoS4erEiSLf7aKiQjp16hLCapq+gIXC3Llzf3HfjBkzzvj4W2+9lVtvvTVQ5Yh6kn0KItwUFJxadFJYWFDHI4U/yI5mUYuc0SzCic1WTWlpCboYIwDHjuWGuKKmT0JB1CIjBRFOcnNzADClR6EYdOTmZoe4oqZPQkEIEbays48AoI83o48zcvz4MWnvHmASCgI4tfrI7XaHthAhTnPkyGEADAkm9PFmVFUlJ0dGC4EkoSBqkZYCIpwcOpSFolfQx5kwJHo3rR0+nBXiqpo2CQUBnLrAXFEhu5lFeHA4HOTmZqOPN6HoFAyJFgCysjJDXFnTJqEgUFUVt9s7T3v67lEhQunIkUOoqoohyRsG+jgjikEnoRBgEgqCsrJS30ihuPhEiKsRwuunnw4CYEgyA96VcfpEE3l5x6mulr5ngSKhIGoFQXl5mazuEGHh0KGfADAkmn33GRItaJrm+zPhfxIKgsLCwlpfFxcXneGRQgTPoUNZKGY9Ouupxgs1ASEXmwNHQkFw4oQ3FHSWJOCXISFEsFVUlHPiRBGGBFOtDZWnQuFQqEpr8iQUBEVF3hAwRHvblZ/egEyIUDh61LtpzZBgrnW/LkqPYtJzNPtwCKqKDBIKghMnvNcU9FGpJ7+WUBChlZNzFAB9fO0DdRRFQR9vpLCgALvdHorSmjwJBUFpaTGKzojOHHfy65IQVyQi3fHjxwDQx/3ylDVDrPe+vLxjQa0pUkgoCMrKSsFgQTF414OXlpaGuCIR6fLyjgOgjzb+4s90scZajxH+JaEQ4TRNo6qqGkVvAsUAig6brSrUZYkIV1RUiC7KgKL/ZdfemqCQBRGBIaEQ4ZxOJ6rqQdEZURQFRWekulr6H4nQ8Xg8lJQU11qKerqa+2tWzQn/klCIcDXtLRTl5PGnis53nxChUF5ejqZp6KJ+/UheXZQ3FGSaMzAkFCKcx+Px3lB0vv/67hMiBGr6b+nMvx4KikFB0StUVEifrkCQUIhwv3b6phzJKUKpoqIcAMV0hlBQFBSTTjr6BoiEghAirFRXexc66ExnfntSTHqqqiqDVVJEkVCIeCdHBb5WAgoaMlIQoVPTAVUx1hEKRh02mw1VVYNVVsSQUIhwv/ilUhRUj/yiidCpGSkoxl+fPgJQDN63Ljkp0P8kFCKc0+kAQFEMJ/+rl9bZIqRstnqMFE5OLcm5Cv4noRDhfP1jdCdDQWfAbpdhuQidqqqTI4U6rinojDWhIBst/U1CIcKVlHj7HNW0uFAM3kNMalaACBFsNauKai40V+05QdWe2icC1qxMkhVI/hewULjvvvsYOHAgEydO9N1XWlrKDTfcwOjRo7nhhhsoK/OuM9Y0jccff5xRo0YxadIk9u7dG6iyxM/4zlIwWgFQjNHAqXbaQgRbWVkpKKCc3KfgzK3CmVt7RKCzeP9Mmjf6X8BCYdq0abzxxhu17ps3bx4DBw5k5cqVDBw4kHnz5gGwceNGDh8+zMqVK3nsscd45JFHAlWW+JnsbG+LYp05AQC9Ob7W/UIEW0FhvrfvkfLLvkc1alpdFBYWBKusiBGwUOjXrx/x8fG17luzZg1Tp04FYOrUqaxevbrW/Yqi0Lt3b8rLyykokH/sYDh06CdQ9L622TpLIgBZWXIGrgi+qqpKysvK0Mf8sjvq6fQnO6XWtNgW/vPrHacC5MSJE6SleU/3SktLo7i4GID8/HwyMjJ8j8vIyCA/P9/32DNJTLRiMJx52ZqoW0lJCdnZR9FHp6OcbHOhM8ej6E3s27eHlJSYOj+tCeFvR47sB04du3kmuigDOrOeQ4cySU2NDUZpESOooXAmv9ZWoT5vRiUlshytITZs2AiAIbqZ7z5F0aGPzuDEiaPs3Pk9bdq0DVF1IhJt2rQNAEOKpc7HKYqCIdlM0bEidu/+kWbNWgSjvCajriAN6uqj5ORk37RQQUEBSUneg+IzMjLIy8vzPS4vL++sowTRcF9/fTIU4lrVut8Q17rWnwsRDKqqsm3bZhSTDmNq1Fkfb2oRA8DWrZsDXVpECWoojBgxgsWLFwOwePFiRo4cWet+TdP47rvviI2NlVAIsJycbDIzD6CPTkdnjMae/x32/O8AMMQ0RzFY2Lz5SxwOOQdXBMfWrZsoKyvF1CIGRXf2mQJTMyuKQce6davl59SPAhYKc+bM4corr+TQoUMMGTKEjz/+mNmzZ/P1118zevRovv76a2bPng3A0KFDadWqFaNGjeLBBx/k4YcfDlRZ4qTPP18CgCmxMwDuiqO4K7wrjhRFhzGhA1VVVWzYsC5kNYrI4XQ6Wbx4AegUorrEn/0b8La6sHSMo6KinBUrPg9whZEjYNcU5s6d+6v3v/3227+4T1EUCYIgysnJZuvWzejMCehjmv/qY0yJnXEV7+fzzz/lssuGEhVlDXKVIpJ8/PH7FBYWYOkYh95a98qj01k6JeA4XMHSpYvo1esi2rRpF8AqI4PsaI4wmqbx3nv/RdM0zKkXnvGCvmIwY0zqSnl5GUuXLgpqjSKybN78FWvWrEQfa8TaPemcvldn1BHdJxWPx8O/X37Ru/FNNIiEQoT58sv17N+/D31Mcwyxvz5KqGFK7orOGM3KlV+QlZUZpApFJPnmm+28+earKEYdMf3TUfTn/pZkSrcS1TWBosICnnvuSSorpfVFQ0goRJDc3Bzee+9tFL0JS0afsz5e0RkwN+uHqqq8+uq/fN0rhfCHdetW8/LLL6LpIHZQBoZ403k/V1S3RCzt48jNzeGJJx8hP/+4HyuNLBIKEaKysoJ//fsfuFxOzBn90J3scXQ2hugMTMndKCoqYN68f8v5zaLBXC4X7733Nv/733/AqBA7KANjUt37Es5GURSsvZKxdIonP+84jz32IHv37vFTxZFFQiECOJ1O/vnP58jPO44xqSvGn+1LOBtTak/00Rns2vWt73qEEOcjJ+cojz32IGvWrEAfZyRuWHOMyQ0LhBqKohDdM5noi1Oottt4/vmn+OCD/+F0Ov3y/JEiLHY0i8BxOp38619zycw8iCGuNea0Xuf8HIqiI6rFIKqPrGH9+jWYzRZmzrxaWmCIenO73axYsYzFSxbicbsxt40l+sJk3wlq/mRpG4ch3kzl9gJWrfqC7/fu5vrrbqJz565+f62mqN7/Ips3b+bdd98FoKioiEOHDgWsKOEfDoedF174O99/vxt9dDMszQac9xu5ojcS1WooOlMcK1Ys4/3335aDeES9/PDD9zz00D0sXPghml4jdmA6MRenBiQQahgSzcSPaIGlfRzHj+Xy9NOP8uabr1JeXhaw12wq6jVSmDdvHhs2bKCwsJBrr70Wt9vN/fffzwcffBDo+sR5Ki8v48UXn+PQoZ8wxLbE0mIgitKw5oE6YxRRbUZgO7qONWtWUlVVyQ033IzRWP915SJyFBTk8/HHH7Bzp7efkbl9HNYLEtGZgtPEUjHoiO6dgqlVDFXfFfH11xv55tsdTJ50BSNGjJaf2zOoVyh89tlnLFy4kBkzZgDeXkWVlZUBLUycv+PHj/GPfzxDUVEhhvi2WJr193VBbSidwYK19QiqczayZcsmSkpK+NOf7iI6OsYvzy8av6qqSpYuXcSaNSvxeDwYEs1E9045a+fTQDEmW4gf3gJ7Vjm2fSV8+OF7rFm7ipkzrqJPn/4yDfoz9QoFi8Xyi1SVv8jwtHfvHl5++UVstmpMKd0xpfTw+7+VYjBjbT0c+7Et7N+/j8cff4g77ribjIxmZ/9m0WQ5nU7WrFnBZ8uWYKuuRmc1ENMjDVOL6JC/Xyg6haiO8ZhbxWD7sYSirEJefvlF2rfvyIwZV9GlS7eQ1hdO6hUKGRkZ7NixA0VRTq5Zf5VOnToFujZxjtauXeWd69fA0mwAxoTAbflXdAYsLQbhKNhFfv6PPPbYg/zxj3dywQU9AvaaIjypqsrXX29k8eIFlJQUo5h0WHskYekQd16b0QJJZ9YT3SsFS4d4qr8vJisrk2eeeYwLL7yI3/zmSlq2PLeVeU2RotVjfWFhYSH33HMP27ZtQ1EU+vbty3PPPUdycnIwaqyjLtm5CODxePjgg3dYu3YVisGMpcVgDNbUc3qOysxPAYjpOPmcX99VmoU9bwc6Ba655ncMH375OT+HaHw0TWP37u9YsOADcnNzUPQK5g5xRHVO8Ot1g5Ll3kaNiWNb++05a7iK7VR/X4y7yI6iKAwaNISpU39DUlJo39sCra7zFM4aCqqqcuDAAbp27YrNZkNVVaKj67fxKdAkFKC6uppXXnmRvXv3oDPHE9XyMnSmc5/fb0goALirC7HnfoXmdnD55WOYNeta9Ho5Fa+pOnLkMPPn/4/9+/eBAubWsUR1S0Rv9f8q90CGAnjDzZVvo/r7YjzlTgxGI2NGj2P8+ClERZ39XIfGqEGhADB9+nQWLlzo16L8IdJDobj4BHPnPsOxYznoY5oT1Xwgiv78VlQ0NBQAVGcltpwvUR1l9O59MTff/CfMZv9sTBLhoayslIULP+LrrzegaRrGDCvW7kkNalFxNoEOhRqapuE4UoltXwmqzU1cXBzTp1/JoEFD0OnCaxqsoRp88lqHDh3IycnxW0Gi4XJyjvL44w9x7FgOxsRORLUcfN6B4C86UwzWNpejj07nu+++4dlnn6C8vDykNQn/8Hg8rFz5OffeexdffbUeXayRuMHNiLu0YT2LwomiKFjaxpIwqiVR3RKpqKrgrbfm8dhjD3LoUFaoywuaeo0Ufv/73/PNN9/Qp08frNZTffVffPHFgBZ3NpE6Ujhw4EdefPHv2Gw2zGm9MSZ1afDqDn+MFGpomgf78e24yw6Tnp7BX/5yP8nJKQ1+XhEaWVmZvP32m2RnH0Ex6bFekIi5bWy9Tkfzh2CNFH7OU+2mem8xzuxKFEVhxIhRXHHFzFrvgY1Vg6ePFi369X76V1xxxflX5QeRGAq7d3/Hv//9Ai63y7vCKL6tX57Xn6EA3qG4s3A3zhP7SExM4i9/uU8OV29knE4nixZ9zMqVn3vP32gdg7VnMjpzcK8VhSoUargKbVR9W4Sn0kVCQiI33jibHj3OvV1MOGlwKISrSAuFrVs38frrL6NpCpYWg856HsK58Hco1HAU7cNZuIuYmFjmzLmHtm3b+/X5RWAcOvQTr7/+Cnl5x9BHG4m+OAVjamguuoY6FAA0j4btQCm2H0tB0xg6dAQzZ17TaC9ENzgUbr/99l+dnpDpo+BZt2417777FigGLK0uw2BN8+vzByoUAJwlP+HI247ZbOGOO/5C164X+P01hH+oqsry5Z/xyScfoaoqlg5xWLsnBbRP0dmEQyjUcJc6qNxZiKfMSVp6OrfcfFuj/KBTVyjoH3nkkUfO9gR2u522bdvStm1bmjVrxg8//EDLli0ZMmSIP+s8Z9XVTb8lrqqqfPLJhyxYMB/FYCGq9XAMUf6fn3cW7wfAlNTF78+tj0pCZ47DUXqELVu+Ji0tjZYtQ/8LLmorKyvl3//+Bxs2rEUx64m9JB1Lh/igXTs4E3umt4ldVMf4kNYBoLMYMLeNRfNolB09wVdfbcBsNtOhQ6eQ79o+F9HRZ245cl7TR06nk1tvvZU333yzQYU1VFMfKTidTt5881W2b9+CzhRzskvpmRO+IQI5UqjhrsrDnvM1mupi6tTfMGnSFY3qF6kp27dvL6+99hLl5eUYM6zE9EkN+rWDMwmnkcLpnPnVVO0oRHV46N27DzfddHOj6QHW4CWpP6coiixRDbC8vOM88cRDbN++BX1UKtY2owIWCMFiiM4gqu3l6IzRLF68gJdemiuNFUNMVVU+/fQTnnvuScorKrD2TCJ2YHrYBEI4M6VbiR/ZAkOqhe++28kjj9zPTz8dDHVZDXbO1xQ0TWP//v0MHDiQesw8BVRTHSls2fI1b7/9Bg6HA2NCB8zpF6PoAvtLGoyRQg3VbceeuwlPdQFJScnceuvtdOggvbSCraSkmHnz/s3+/fvQRRmIGZDW4GMxAyFcRwo1NE3Dtq8E24+l6HQ6pk2bydixE8N6w5tfl6Tq9Xpat25N7969/VNdAzS1UCgrK+W99/7Ljh3bUHRGzBl9Mca3CcprBzMUADRNxVn0A86ivSgKjB07kSlTpmMyNY2NUOFu+/YtvPPOf6iqqsTU3Er0xalBO+fgXJUsP4qmaSSNC87vwvlyFdio3FGAavfQrVt3brzx5rDdn+PXJalOp5OysjJSU8+t4VogNJVQ0DSNTZu+5IMP/kd1dRX6qBQszQcEdboo2KFQw11VgOP4NlRXJWlp6dxww2xpYxxAFRXlvPfef9m2bQuKXsHaIwlz+7iwvbbjLnNStjYHNNDFGIkdkB7WO6hVh4fKnYW48qoxWyxcdeVvueyyYWH399vgULjrrrt49NFHMRqNTJkyhZKSEm6++WZuuukmvxZ6rppCKBw5cpj333+bgwf3o+gMmFJ7YUzsGPQfolCFAoCmunEU7sFVfADQuOSSS5kx42oSE5OCXktTpaoqX321gY8//oCqqkoMSWZi+qSijw3fN1iAkpXZqJUu39e6GCOJo8O7vXVND6XqPSfQXCpdunTj2mtvoEWLlqEuzafBoTB16lQWL17M8uXL2bRpE/fddx8zZ85k6dKlfi30XDXmUKioKGfRoo/ZsGEtmqZhiG2JOf0idMbQdKANZSjU8NhOYM/biWovxmQyM3HiFMaMGY/RGN5vXOHu8OEs3n33v2RlZaIYdER1S8DSMT7sPr3+nGp3U/L50V/cnzi+NTqL/7ux+pun2k3Vd0W48qrR6XSMHj2eiROnhkWbjLpCoV5/s263G4Dt27czdOhQoqKiGnQR5b///S8ff/wxiqLQuXNnnnrqKQoKCpgzZw5lZWVccMEFPPvss01yftnlcrJ69QqWLl2M3W5DZ47Dkn4xhuiMUJcWcvqoZKxtR+EuO4SjcDeffPIRGzasZfr0K+nf/5KwvnAXjgoK8lm06GO2bt0EgKlFNNaeyQFpbx0ImufXP6+e6f5wo7caiLs0A+fxKqp2nWD58s/46qv1TJo0jeHDL8dgCM9/h3qNFO644w4qKirIysri888/R6fTMWvWLJYsWXLOL5ifn89VV13F559/jsVi4Y477mDo0KFs2LCB0aNHM2HCBB566CG6du3K1VdfXedzNaaRgqqqbNu2mQUL5lNcfAJFb8KU0uPkVFHo3+zCYaRwOs3jxFH0A66SA6CptG3Xnlkzr5HrDfVQVlbKZ58tYf361Xg8HvQJJqJ7JGNMa1wtGTxVLkpXZP/i/oQxrdBHh7Yj8LnS3Cq2zDLsB8rQ3CopKalcccUMBgy4NCQfdho8UnjmmWf46quv6NKlC1arlfz8fP785z+fd0Eejwe73Y7BYMBut5OamsqWLVt4/vnnAW+jvX/9619nDYXGYt++vXz40XscPXIYFB3GpK6YUy5A0Te9kZC/KHoTlvTemBI74ijczeFDWTzzzGP07t2H3/zmSpo3l+Z6P1deXsbnny9l3bpVuFwu7xnJ3dMwtQz9GcmRTjHosHZNxNIuzntG9KEiXn/9ZZYuXcyUKdPo1y98RsL1nj4aMWIEOp2OAwcOcPDgQUaNGnVeL5iens6NN97I8OHDMZvNDBo0iO7duxMXF+cbTmVkZJCfn3/W50pMtGIwhOcyOoAjR47w1ltvsXPnTgAMcW0wp/Y8r5PRgiEceyPqTDFEtbgUT1IXHPnf8d13O9m16xtGjx7N1VdfTVKSXIwuKyvjk08+4bNly3A6HOiiDER3Twlqe2tRP74zojvGY9tfSt6RY7z22r/4/PMlXHXVVQwaNCjk4VCvULjuuut49913qaqq4qabbqJz5858+eWXPP300+f8gmVlZaxZs4Y1a9YQGxvLHXfcwcaNG3/xuPp8sikpqT7n1w+GkpJiFi1a4DudSm9Nw5zWG31UeL6BeeylaC4boFH50zKiWgxCb0kIdVm16KOSiWozAk/lMRwFu1ixYgXr1q1j7NiJjB07EYsl/DZdBVpFRTnLly9jzdqV3jCw6InulYy5bRyKXsIgnOmjjcRcnEpUlwRs+0rIzs7m2WefpUWLlkyZMp2LL+4X0HBo8PSRpmlYrVaWLVvGzJkzue2225g0adJ5FbNp0yZatmzp+4Q3evRovv32W8rLy3G73RgMBvLy8khL828X0GCw2Wx88cVSVqz4HJfLic4cjyWtF/roZmE9fLflfg14RwmaswJ77tdEd5gQ2qJ+haIoGGJboI9phqs0C2fR93z66SesX7+GqVN/w2WXDYuIc6EdDgerVn3Bss8/xWG3o7PosfZKxtI2FkUfHlMQon700UZi+qYR1TUR248l5Gbn8PLLL9K6TVtmzbyGbt26B72meoWCw+HA6XTy5Zdfct111wGcd4o1b96cXbt2YbPZsFgsbN68mR49ejBgwABWrFjBhAkTWLRoESNGjDiv5w8Fj8fDl1+uZ/HiBZSXl6EYojA364cxvl1YXESui+q2oTlrX7BXnRWobhs6Q3hemFQUHabEjhjj2+A88SMVxft55503WbV6ObNmXkPPnr3COoTPV80mx08++YiSkmJ0Jj3WnklY2sdJGDRy+piT4dAlgep9JRw9cpi///0JLrzwImbOvDqo19DqFQrjx4/nkksuoX379lx88cUUFhZiNp+59WpdevXqxZgxY7jiiiswGAx069aNWbNmMWzYMO666y5eeOEFunXrxowZM87r+YPt++93MX/+exw7luPdfJbSA1NyVxRdeC43+wXVc273hxFFZ8Sc2hNjQkecRXs4fuwQL7zwLN2792TWrGuaVHvu4uIT/Oc/r/HDD9+j6BUsnROI6pKAzihh0JToY03E9k/H3clB1Z4T7N79LXt/2MP0aTMZPXp8UK431LvNRXl5OTExMeh0OqqqqqisrCQ9PT3Q9dUplEtSjx/PZf78d9mzZxcAxvj2mFJ7ojOG56frM1GdlVT99Nkv7o/uMDFsL4ificdeiqPgWzxV+SiKwtChI5g6dQZxcXGhLq1BduzYyltvzcNms2FMjyL6otRGs9egIZrSktTzoWkazmPVVH9XhOrw0KlTF2655XYSExMb/NwNbp2taRorVqzwLRktKSkhNze3wYU1RlVVlbz//ts8+OA97NmzC701DWu7MVia9290gdDU6C0JRLUaRlSrISjGWNavX8O9997F8uXLfBswG5udO7fxyiv/xO5yEH1RCrGXZkREIJzOZDLRvHnzJrmZtS6KomBuEU385S0xNbdy8OB+nnv+SSorA/thuF6h8NRTT7FlyxbWrFkDQHR0NE8++WRACws3qqry5Zfrue++P7N69QowWLG0HExU6+HoLQ1PbuEfiqJgiGmOtf1YzOkX43B5+Oij93jooXvZt29vqMs7J5mZB3j1tX+BXiFucAaWduHbuC5QTCYTt9xyC6+99hq33HJLxAUDeJexxgxIx9IxnuPHcnnhhWfxeAI3vVuvUNi6dSvPPfecb9lfYmIiDocjYEWFm+zsozz99P/x1lvzqKq2YUrrhbXdOIyxLSPul7SxUBQdpqTORHeYgDGxI3l5x/j735/g1VdforS0JNTl1cvq1SvwuN3E9E/DEIbnHARDSkqKb0/UqFGjSEkJz1bUgaYoCtaeSZiaW8nK+onMzAMBe616hYLZbK715qeqasAKCieqqvLFF0t59NEHyMw8iCG2JdZqoiC7AAAgAElEQVT24zAndwv4oTfCPxS9GUtGX6xtR6OzJLFt22b+9uBf2blzW6hLO6s93+9CZzVgTI/cacmioiJWrVoFwKpVqygqKgpxRaGjKArmtt7rY7t3fxew16nX5GTnzp359NNP0TSNnJwc5s2bR58+fQJWVDgoLj7B66+/zP79+1AMFqJaDcIQ0zzUZYnzpI9Kwtp2FK6Sg9gKdvHvf7/A4MHDuPrq68J241uUJQp7hR1UIEI/gzidTl599VUWLFhAUVERTqeT0PcYDR3N4Z02iooK3AeFeo0U7r33XrZt20ZhYSEzZ85EVVX++te/BqyoUMvPz+OJJx5m//59GGJaYG03TgKhCVAUBVNSZ6LajUZnTuSrr9bz/PNPYbOF5874vn0HoLlU7JmloS4lpJxOJ8eOHcPpdIa6lJBSXSq2g2WA92cjUM46UlBVlZ07d/L4448HrIhwkp+fx7PPPk5JSTGm1F7ePQdy3aBJ0Zvjsba7HPuxbfz000Hmzn2GOXPuISoqvD6Djhkznu3bt1CytxjFrMfStnEvrRXnT3OrVGzOw1PuZPjwy8nIaBaw1zrrSEGn0/HKK68ErIBw8/rrL1NSUow5rTfmlG4SCE2UouixNB+AIa4NP/10kIULPwx1Sb+QmJjEnDn3Yo2OpuqbIqq+K0LzRMb1PHGKu8xJ2bpc3EV2+vTpxzXX/C6gr1ev6aMePXqwe/fugBYSDrKyMsnKykQf0xxTctdQlxNUkbgWXFF0WJoPQDFY+eqrjVRXh980UosWLbnv3odp3rwF9qxyytYfw10SOSv/Ipmmatgyyyhfn4unwsXIkWOYPftPAd/VXK8LzTt27OCDDz6gTZs2tY6SW7BgQcAKC4VvvtkBgDGhfYgrCa6ateCjRo1i1apVvPrqq6EuKWgURYcxvi3OEz/www/f07dv/1CX9AstWrTkwQcfZ/78/7Fhw1rK1uVibhuLtXsSOnOEXoFu4lyFNqp2ncBT7sQaHc1NN97CRRcFZ3FPvULh/vvvD3QdYSE52bsGWnNH1iexn68FX7BgAWUhrimYNI/33zuc18CbzWauv/739Ot3Ce+9/zbHD+fiPFZFVJcEaYjXhHgqnFT/UIIztwpFUbjssmFMnz6LuLj4oNVw1lDYv38/JSUldOnShbZt2wahpNDp1KkzAK7SLIwJbVGUyPgUVrMWvGakUFRUhLFVqKsKDtVlw12Zi8lkahQN9C64oAf/98hTrF27kiVLFlK9pxh7ZjlR3RIxt46RQ3UaKdXmpvrHEhyHK0CDdu06cM0119O+fceg11JnQ7x33nmHf/7zn7Rr145Dhw7x6KOPMn78+GDWVyd/N8TTNI158/7N1q2bMCZ0xNKsr1+fPxzVNMQzmUykpKT41oI3xoZ450rTPNiOrMNjK2LmzGsYOzb8zpCoS2VlBZ9/vpTVq5fjdrvRxxiJ6pbYZI7fjISGeKrdg+1AKY5D5WgejYyMZkybNos+ffoF9N/wvA/ZmT9/Pp999hkZGRlkZmbyt7/9LaxCwd8UReF3v/s9ubk55ORkgqJgTr8o7M9E8IeateCRQvM4seV+jcdWRP/+AxkzpvH9XMfExDJz5tVcfvkYPv30E776agOV2wvQ7zd5w6G5tUmEQ1OkOjzYDpbhyCpHc6skJiUxedI0Bg8eGvKDouoMBZPJREZGBgAdO3aMiH5HZrOFO++8m7lzn+HYsYOoriqimg9E0TeNTybCOzqy5WxEdZTTu/fF3HDDHxr1m2dSUjK/+90fGD9+MkuXLmLTpi+p3JqPPt6EtVsixmYSDuFCdXqwHyzD/pM3DOLjE5g4cSpDhgzHaAyP95g6Q6GyspINGzac8euhQ4cGrrIQSkpK5v77H+GVV15k7949VB9ehaXlIPTm4F3sEYHhrjyO/dgWNI+Dyy8fy5VXXhvyg9L9JS0tnZtuusUXDlu3bqJiSz76BBPWbkkYM6IaVTic6Zzpxnj+tOpSsWeWYc8sQ3OpxMXFMX78ZIYNuzzsloHXeU3ht7/97Zm/UVF45513AlJUfQX6kB23281HH73P6tXLUXQGzBn9MMa3CehrBltTOmSnLpqm4izai7NoL3q9gWuuuZ5hw0aGuqyAys3NYenST9i+fSuapmFIMhPVLRFjWuMJh5KV2aiVLt/XuhgjiaMbzyoIza1i/6kM28EyNKdKTEwM48dPYfjwy8/79Ep/qOuaQr1PXgtHwTp5bfv2LfznP6/hcDgwJnXBnNaryVxniIRQ0DxObMe24Kk8RlJyCn/8f3fSrl3k7EXJyclmyZIF7Ny5HQBDigXrBYkYU8K/+6q7zEnZ2hzQvIEQOyAdQ3x4fbL+NZpHxZ5Vjv1AGarDg9VqZdy4SYwcOSYsGjCedyhkZmbW+cQdOwZ/udTpgnkc5/Hjubz00lzy8o6jj04nqvmlKIbQJb2/NPVQ8DjKsed8ieqsoHv3ntx8823ExDT+/6/zceTIIRYtWsDu3d8CYEyLwnpBYtif1VCy/CiappE0LvxH6Zqq4Thcge3HUlS7G4vFwpgxExg1alytjb+hdt6hMGLECN/t48eP+36ZKioqaN68OWvXrvVjmecu2Gc0V1dX88YbL/Pdd9+gM8US1XoYOmN0UGvwt6YcCu7qQuw5X6J5nIwbN4np02c1mesHDZGZeYBFiz72nURnbGbFekFS2H4CL1l+FIDEseG7j0RTNRzZldj2laBWuzGZTFx++VjGjp1ATMyZ34BDpcHTR48//jh9+vRh3LhxACxfvpwffviBOXPm+K/K8xDsUABv19gFC+azfPlnKIYooloNRW9JCHod/tJUQ8FVkYMjdzOKonHDDbMZNGhIqEsKO/v27WXRoo/IzDwIgKllNNZuiehjwyscwjkUNE3DmVOFbV8JnkoXBoOBYcMuZ8KEKcTHh+/ClPPep1Bj9+7d/O1vf/N9PXbsWP7zn/80vLJGSKfTMXPm1SQkJDB//rvYjq4lqtUw9FFJoS5NnOQqO4z92FZMJhN//OOd9OzZK9QlhaVu3brTtesj7Nmzi08WfcTRI4dx5lZhahWDtWsi+pjwWCIZjjRNw5lbhe3HEjzlLnQ6HcOGjWTixKkkJSWHurwGqVco2Gw2duzYQd++3h2+O3bswGazBbSwcDd69Hiio2P4z39ew3Z0nXfEYA3f3jmRwlWahf34NqKiopgz5146dOgU6pLCmqIoXHhhb3r27MU332xn8ZKF5B7NxpldiblVDFESDrVomobzWLV3ZFDuRFEUBg0awqRJV5CWlh7q8vyiXqHw8MMPM2fOHN8RcA6Hg+effz6ghTUGgwYNwWg0Mm/ev7Flr8fSYjCGmIxQl3VuznTWdCM8g9pZvB9H/rdYo6O5+y/306ZNu1CX1GgoikKfPv256KK+7Ny5jcVLFnL8aC4OCQfg9JFBqS8MBg4czOTJV5CeHrgDb0Kh3ktSnU4nhw4dQtM02rdvHxYbLkJxTeHXfPvtDl555Z+4PSqW5pdgjAu/uc+6VP60DM156u9SZ4olukPj6QOkaRrOwj04T/xAfHwCf/7zvY2iuV04U1WVHTu28umnizh2LAcUMLWMIapLAoa44P7uh/Kagu+awY8leCpcKIrCJZcMYuLEqTRr1niP6PXLPoXMzEy2bt0KwCWXXEKHDh38U10DhEsoAOzfv48XXvw7DrsdU/IFmFJ7NJq9DB57KdWHVgAaOlMslhaDGs3Fc83jwn58K+6KHFJT0/jLX+4nNTUt1GU1Gaqq8s0321ny6Sfk5nib05maRxPVNQFDQnCWZIciFDRVw3G0AvuBMjyV3msGAwcOZuLEKU1iZNDgUFi8eDHPPfccw4YNA2Djxo385S9/YfLkyedVUHl5OX/72984cOAAiqLw5JNP0q5dO+666y5yc3Np0aIFL7zwwlmv3odTKABkZx/lpZfmUlRUgD46HUvzgegM4b0GvEZl5qdomkZspymhLqXePI4y7DlfoTor6Ny5K7feekdYr/hozFRVZdeub1i6dDGHD2cBYMywEtU1AWOA9zkEMxQ0j+rdZ3CwDLXajV6vZ/DgoYwbN6nJXDMAP4TC5MmTefPNN0lNTQWgsLCQm266iU8//fS8Crrnnnvo27cvM2bMwOl0YrfbefXVV0lISGD27NnMmzePsrIy7r777jqfJ9xCAaCqqpLXX3+F3bu/RdGbMadfhCGuTdi3FajM9P5bxnQ8v6APJk3z4Czah/PED6CpjBkzgenTZ2Ew1OsSmWgATdPYu3cPS5cu4uDB/QAYU6O84ZAamB3SwQgFza1iP1SO/WAZqt2D0Whk6NCRjB07odGvJvo1DV6S6n2S1F+9fa4qKyvZvn07Tz/9NODtxGoymVizZg3/+9//AJg6dSq//e1vzxoK4Sg6Oobbb/8zq1cv55NPPsJ+bAv6ssNYMvo26nX/4cJTXYQ9bzuqo4z4+ASuu+5GLrqo6Z97ES4URaFHjwvp0eNC9u/fx2efLWbv3j24Cm3e9hndEgMWDoGguU+2ozjobUdhNpsZMW48o0ePj9hRZ71CoXXr1vzzn/9k1qxZKIrCRx99RKtW59eUKjs7m6SkJO677z5+/PFHunfvzgMPPMCJEydIS/POBaelpVFcXHzW50pMtGIwhOcqmWuumcXIkUN5+eWX+fbbb6nK+hxjQkdMKRc0mimlcKI6ynEU7sZdkQPAuHHjuP7664mObtw7yhuz1NT+DB7cn/379zN//nx27NhB+ZfHMaRavF1ZU8L351zzqNgPVWA/UIpq9xAVFcXkWZOZPHkycXFxoS4vpOo1fXTixAkef/xxNm3aBMCgQYN44IEHSE4+92HVnj17mDVrFh988AG9evXi8ccfJyYmhnfffZcdO3b4HtevXz+2b99e53OF4/TRz2maxvbtW1iwYD5FRYUoOiPG5K6YEjuH1RkN4Tp9pLpsOIu+x1WaBWi0b9+RWbOuoVOnLqEuTfxMVlYmixcv5PvvdwHe9hnRPZIavEPan9NHNauJqvcWo1a7MZvNjBo1jjFjvPuOIkWDp4+Sk5P5xz/+4ZdiMjIyyMjIoFcv7y7TsWPHMm/ePJKTkykoKCAtLY2CggKSkprGDmFFUejffyAXX9yP9evX8Omnn1BZuAdX8X6MiZ0xJXVG0Yd+eW+4UV1VOIv24SrLAk0lI6MZ06dfycUX9w376zORqn37jsyZcw+ZmQf46KP3ycw8QGmeDUu7WKIuSERnCu2o3nXCTtWuE3hKHegNBsaOncD48ZPDsjdRKNUrFDRN48MPP2TTpk0nd/ANYsaMGef1y5mamkpGRgZZWVm0b9+ezZs306FDBzp06MDixYuZPXs2ixcvZuTIptXr3mAwcPnlYxg06DJWrVrOylVfUF30/clw6IQxqQu6JtB1taFUZ4U3DMoPgaaRkprGxAlTGDRoSMiPKRT107FjZ+6772G++WY7H3/8AQVZ+TiPVRPdOxlT8+BP92luleq9xdh/Kgegf/+BTJ8+S5Yun0G9po+eeeYZ9u3bx7Rp0wDvEtWuXbvy17/+9bxedN++fTzwwAO4XC5atWrFU089haqq3HnnnRw/fpxmzZrx4osvkpBQ91r5xjB9dCY2m43161fzxfLPqKyoQNEZMCR0wJTUBZ0x+C12Qz195LGX4jzxA+7ybMB7gPnEiVMZMOBSCYNGzO1288UXS/l06SI8bjemVjHEXJSCYqj/Hp6GTB+5Ttip3F6AWu0mI6MZv/vdH+jcues5P09T0+AlqZMmTWLRokW+JX8ul4tp06axdOlS/1V5HhpzKNRwOBxs3LiWL774jNLSElB0GOPbYkruhs4UvGFtqELBU12E48QPeCqPAdCqVWsmTJhC374DpM11E5Kbm8Nbb80jKysTfbyJ2EvS0UfX75ra+YaC/XAF1d8VgQbjx09i8uRpGI0yVQt+WpJ6+lSRzOn6T82FruHDR7Fp05d8/vlSCgqycJUewhDfBnNK96CGQ7C4qwtxFn2Ppyof8E45TJw4hZ49e8vPVxPUokVL7r33IebP/x9r166ifN0xYi9rFrAzHKr3lWDbV4LVauXWW++ge/eeAXmdpqheoTB48GD+8Ic/cMUVV6AoCosWLWLw4MGBri2iGAwGhgwZzuDBQ0/2nPmEY8cO4y470qTCwVNdhKNojy8MunXrzuTJ0+jSpVuIKxOBZjAYuPbaG2jRoiX/+99bVGzKI25oc/RW/246tGeVY9tXQkpqGn+ecy/p6Y2sSWWI1Wv6SFVV5s+fz5YtW9A0jUsvvZRZs0J/ilVTmD46E1VV2blzG0uWfHKyIZkOY0JHzCndA3IMaKCnj1RnBY6CXb59Bhdc0IPJk6fJ/G6EWr58GR999B76BBPxw1qg6M48OjyX6SPXCTvlG44RGxvHAw/8X5NqTeFPfmmIF46acijUqOlW6dvnoDdiSu6OMakTiuK/C7CBCgXN48RR+D2u0oOgaXTo0IkZM66SMBC8/vrLbN78FdYLk4nqeObdw/UNBU3VKFubi6fcyb33PiQ/Y3U472sKzz77bJ1PfL6rj0T96XQ6+vcfyEUX9WXdulV8+ukiqgu+w1V2CEuz/uijwrMvi6ZpuCuyceR/g+a2k5KSxsyZV9GnT3+5ZiAAmDXrWnbt/hbbvhIs7WJR9A2beXBmV+IpdzJkyHAJhAaoMxSs1uAvjRS/zmg0Mnr0eC69dAgLF85nw4a1VB9ejTGpM+bUnii68GkGp7psOPJ24K7MxWAwMGX6LEaPHo/RGD47uEXoxcXFMWL4KD77bDGOnCosbRp2zcx+qBxFUZg4caqfKoxMdUbzLbfcQocOHbj44ov505/+RGxsLHv27KGyspLrr78+WDWK08TExHD99b/nnnseJC0tHVfxfqoPr8LjKA91aQC4K/OoPrwcd2UuXbp047HHnmHChCkSCOJXDRkyHPB+ym8IT5ULd7GD7t17kpJy/g07xVlGCo8++igHDhzA6XTSsmVLHA4Hw4YNY/v27Tz88MPMnTs3WHWKn+nSpRuPPvo0H330HmvXrsJ2eCXmjH4Y49uEpB5N03AWfY+zaC96vZ6ZV13HyJGjQ74YQYS3lJRUWrVqTXZuNppbPadNbadz5VUDSMdcP6gzFHbs2MGyZcuw2WwMHjyYLVu2YDKZmDVr1nkfsCP8x2Qyce21N9C5c1feemse9mObUZ3lmFJ6BHXeXlPd2I9twV2RQ1JyCn/8f3fQrl3oT+YTjcOFF/YmO/sorkI7pmbnN2XtzLcB0LNnL3+WFpHqjGWTyYSiKFitVlq3bu07l1mn08l0QBjp338gDz30OCkpqTiL9mI/vg1NU4Py2prbQfXR9bgrcujSpRuPPPykBII4J927XwiAq6D6vL5f82i4i+xkZDSTqSM/qHOk4HQ6+emnn7xTA6fdBm97BhE+mjVrwQMPPMqLL/6dw4ezsKsuLC0G+nXZ6s+pbju2o+tQHWUMGHApN954s3xYEOesY8fOREVF4ThWjfVC7ZxHua5CG5pb5cILeweowshSZyjY7Xb+8Ic/+L4+/bYsKww/8fHx3HPP33jxxef48ccfsOdswtLy0oAEw+mBMHz4KK655nq5fiDOi8FgoHfvPmze/BXuYgfG5HM7nMeZ471I3adP/0CUF3HqDIW1a9cGqw7hJ2azhTvuuPtkMOzFfmwrluYD/RrimseF7egGVEcZI0eO4eqrr5MPCaJBBg0awubNX+E4VH5OoaA6PThzq0hLz6BDh04BrDByyEe7JshsNnPHHX+hY8dOuMuP4sj/Fn9tXNdUD7acL1EdJQwZMlwCQfhF164XkJ6egSOnCk+1u97fZ88qR/NoDBs6UkaqfiJ/i02U2Wzm9tvvplmzFrhKDuAqOdjg59Q0DXvedjzVBVx0UV9++9sbJRCEX+h0OsaNmwSqhv1gab2+R3Op2DPLsVqtDB06PMAVRg4JhSYsJiaGOXPuITY2Dkf+t7ir8hr0fK7i/bjLDtO2bXtuvvlPcviN8KtLL72M5OQU7Icq8FS5fPebWkRjavHLE9tsmWVoTg+jR48nKkq6L/iLhEITl5ycwm23zUGv12PP3YzqOr9lf+6qAhwFu4iPT+S22/7sW54shL8YDAamTZsJqkb1DyW++6N7JhPds3aPL9XuwX6wjNjYOEaPHh/sUps0CYUI0LFjZ66++rdoHgf23E3nvIdBdduxH9uMTqfwxz/eQWJiYoAqFZFuwIBLadWqNc7sStylZ172Xv1jCZpbZcqU6Vgs57ZaSdRNQiFCDBt2OX379sdjK8J5Yl+9v0/TNBx5O9DcNqZNm0nHjp0DWKWIdDqdjhkzrgKgem/xrz7GU+XCcaictLR0X+8k4T8SChFCURSuv/73xMcn4Czai8dRVq/vc1dk467IoXPnrowdOzHAVQrh3eHcuXNXXPk23CW/HC3Y9peCBlOmTPedGy/8R0IhgkRHx3DddTeBpuI4vv2sy1Q1jxNH/jcYjSZuuGG2LPkTQaEoCpMnTwPAdqD2SiTV7sZxtJK09AwGDLg0FOU1efJbHmEuuqgPF13UB4+tCHf50Tof6yjai+a2M3HiFDnnVgRVt27dadGiJc5jVai2U/sW7IcrQNUYdfkY+ZASIPK3GoFmzboWvd6As3A3muYBwBDbGkPsqeMOVVcVrpKDJCenMGbMhFCVKiKUoigMGzYSNHDkVvnud2ZXYjQaGTjwshBW17RJKESgtLR0hg8f6X3jLz0MgCW9N5b0Uw3FnEU/gKZyxRUzZPmpCImLL/b2MnIe94aCp9KFp8JFjx4XyqmQASShEKHGjZuMwWDAdWLfL5aoqi4brrJDpKXJvK0IncTERFq3bov7hAPNo+EqrDkzQbqhBpKEQoRKTExk4MDBqK5KPJW1dzq7SjNBUxkzZrzsWhYh1aFDJ1A13GUO3MWOU/eJgAlZKHg8HqZOncrNN98MQHZ2NjNmzGD06NHceeedOJ3OUJUWMUaOHAOAszTTd5+mqbhKs7BYohg4cHCoShMCgFatvNe5PBUuPBVOdDodzZu3CHFVTVvIQuGdd96hQ4dTJ3Q999xz/O53v2PlypXExcWxYMGCUJUWMVq3bkOrVq3xVOWhebwh7KkuQnPb6NdvgOwUFSFXs+pNrXThqXSTmpomo9cAC0ko5OXlsX79en7zm98A3l2zW7ZsYcwY7yfXK664gjVr1oSitIjTv/9A0FTclbkAuCtyTt0vRIglJSUB4Kl2ozk9JCYmhbiipi8k2wGffPJJ7r77bqqqvKsKSkpKiIuL8+1OzMjIID8//6zPk5hoxWCQTw0NMXToIBYu/BB3VT7G+HZ4qvIwm80MGtRPjtYUIRcd7f399pR7R7JpaSmkpsaGsqQmL+ihsG7dOpKSkujRowdbt2494+Pq06e/pOT8On6KU6zWJGJiYqmqLkB121Gd5XTqcSGlpXbAHuryRITTNA2dToen0ttK22i0UFhYEeKqGr+6gjXoofDNN9+wdu1aNm7ciMPhoLKykieeeILy8nLcbjcGg4G8vDzS0tKCXVpE0ul0tG3bnu+/34Wnyjs6a9u2fYirEsJLURSs1mgqK71BIOcmBF7Qryn8+c9/ZuPGjaxdu5a5c+dyySWX8PzzzzNgwABWrFgBwKJFixgxYkSwS4tYrVu3AcBVfuTk121DWI0QtUVFRf3qbREYYbNP4e677+att95i1KhRlJaWMmPGjFCXFDFqVnh4Tp7MJn2ORDgxm0+tgpMVcYEX0r6zAwYMYMCAAQC0atVKlqGGSEpKqvfGyZ3NKSkpIaxGiNrM5lNtVkwmcwgriQxhM1IQoRMXF++7bTSasFhkiC7Ch9Fo+tXbIjAkFASxsXGn3Y6t18ovIYLFYDi1NNpolEN1Ak1CQfzsQp6s7hDh5fS9SLKbOfAkFARGoxGdzvvLZrHInK0IL4qi+9XbIjDkb1gApz6ByZytCDenT2fKzGbgSSgI4NQvmxxxKMLN6ed9qKpaxyOFP8g7gABOfRqTi8wi3Hg8EgrBJKEgatE0LdQlCFGLx+M+7baEQqBJKAgAaqJAQkGEG4/Hc9ptdx2PFP4goSC8TobB6b+AQoSD2qEgP5+BJqEggFPDcpmzFeFGVSUUgklCQQCnfvFkeC7CzekzmjK9GXgSCgJVVX2/bDJSECKySSiIWkEgqztEuDl974y0uQg8CQVRa0guw3MRbmrObvfelnPDA01CQdQaKcj0kQg3JtPprbMlFAJNQkFwapfCz28LEXqnH6wjJ68FnoSCqEWmj0S4Ob21u4RC4EkoiFqk95EIN3LeR3BJKIif9aiXUBDh5fQgOD0gRGBIKIhaowNpnS3CTe1QkJFCoMk7gKgVBDJ9JMLN6aMDWX0UeBIKolYonL4mXIhwcProQD60BJ6EgkBRFPR6bxjIjlERbuTc8OCSUBAA6PXeH4XTNwoJEQ5O36cgAk9CQdQic7Yi3MgHleCSUBAneedq5VOZCDdxcfEAdOjQMcSVRIagX1U8fvw4f/3rXykqKkKn0zFz5kyuv/56SktLueuuu8jNzaVFixa88MILxMfHB7u8iGc2SyiI8JKUlMwjjzxJUlJyqEuJCEEfKej1eu69916++OILPvzwQ95//30yMzOZN28eAwcOZOXKlQwcOJB58+YFuzSBtBEQ4al167bExMSGuoyIEPRQSEtLo3v37gDExMTQvn178vPzWbNmDVOnTgVg6tSprF69OtilCWT1kRCRLqSL0nNycti3bx+9evXixIkTpKWlAd7gKC4uPuv3JyZaMRjkTcwfapZ/W61mUlPlE5kQkSpkoVBVVcXtt9/O/fffT0xMzHk9R0lJtZ+rilw1zVGrqx0UFlaEthghREDV9cEvJKuPXC4Xt99+O5MmTWL06NEAJCcnU1BQAEBBQQFJSUmhKE1IQzwhIlrQQ0HTNB544AHat2/PDTfc4Lt/xIgRLF68GGlS/GcAAAWtSURBVIDFixczcuTIYJcW0aR7gBACQjB9tHPnTpYsWULnzp2ZMmUKAHPmzGH27NnceeedLFiwgGbNmvHiiy8GuzSB9JYRItIpWiM+akvmvv3nww/fY8WKZfy//3cnffv2D3U5QogAquuagoSCALzXebKzj9C2bXs5U0GIJk5CQQghhE/YrT4SQggRniQUhBBC+EgoCCGE8JFQEEII4SOhIIQQwkdCQQghhI+EghBCCJ9GvU9BCCGEf8lIQQghhI+EghBCCB8JBSGEED4SCkIIIXwkFIQQQvhIKAghhPCRUBBCCOEjoSDYuHEjY8aMYdSoUcybNy/U5Qjhc9999zFw4EAmTpwY6lIihoRChPN4PDz66KO88cYbLFu2jM8++4zMzMxQlyUEANOmTeONN94IdRkRRUIhwu3evZs2bdrQqlUrTCYTEyZMYM2aNaEuSwgA+vXrR3x8fKjLiCgSChEuPz+fjIwM39fp6enk5+eHsCIhRChJKES4X2t9pShKCCoRQoQDCYUIl5GRQV5enu/r/Px80tLSQliRECKUJBQiXM+ePTl8+DDZ2dk4nU6WLVvGiBEjQl2WECJEpHW2YMOGDTz55JN4PB6mT5/OrbfeGuqShABgzpw5bNu2jZKSEpKTk7ntttuYMWNGqMtq0iQUhBBC+Mj0kRBCCB8JBSGEED4SCkIIIXwkFIQQQvhIKAghhPAxhLoAIULF6XQyd+5cVq9ejcFgwGKx8Kc//YnLL7+8zu/bunUrLpeLwYMHB6lSIYJHQkFErEceeYTq6mqWLVuG2WzmwIED/P73vyc+Pp5+/fqd8fu2bdtGdXW1hIJokmSfgohIubm5TJw4kXXr1pGQkOC7//3332fFihX07duX6upq7rnnHgBeeuklqqurmTp1KjfeeCOqqpKWlsaECROYPXs269at46WXXsLtdqPT6Xj66afp2rUrGzduZO7cuXg8HpKSknj00Udp06YNW7du5YknnuDCCy9k165dGAwGnn32Wf71r39x8OBBmjVrxksvvYTVasXpdPKPf/yD7du343K56Ny5M4888gjR0dGh+usTTZhcUxAR6cCBA7Ru3bpWIAD07t2bH3/88Yzf16VLF6688kqmTp3KkiVLmD17NocOHeJv/7+9uwdpJAjAMPzGxU0TGwur4A8RE5NGG0EQC0khJmChXcpAqjRCEETBiI34V1lYWFiLEGJQsQliYWFlI4FAIElhJwhOoaLJFXKDFt4hl6vyPdXuwszObrHfzswyu7LC7u4uJycnHB0d4ff7eXh4YHFxke3tbQqFAvF4nEwmY+uqVCokEgkKhQIjIyMkk0mWlpY4Ozujo6OD09NTAA4ODujq6uL4+Jh8Pk9PT49+hiT/jYaPpC21soN8fX3N5OQk/f39ALiui+u63NzcEAqFGBwcBGBubo61tTWMMQAMDAwwPDwMQDgc5v7+3i5jHolEqNVqABSLRYwxXFxcAB9zIaFQqGXtF/lMoSBtaWhoiHq9zuPj45fewu3tLcFgEMdxaDQa9vjLy8u3dX0XMM1m84/LkLuua7cdx8Hr9X7Z/33OZrPJ6uoq4+Pjf78wkX+k4SNpS36/n+npabLZrH34lstl9vf3SafT9Pb2cnd3R6PRwBjD5eWlLevz+Xh6erL7ExMTXF1dUa1WgY83eWMMo6OjlEolKpUKALlcjnA4jM/n+1Fbp6amODw85Pn5GQBjjK1TpNXUU5C2lc1m2dnZYWZmhs7OTrxeL8vLy4yNjfH6+sr5+TmxWIy+vj4ikYgtF41GyefzzM7O2onm9fV1FhYWeH9/x3EcNjY2CAaDbG5ukslkeHt7o7u7m62trR+3M5VKsbe3x/z8PB6PB4/HQzqdJhAItPJ2iAD6+khERD7R8JGIiFgKBRERsRQKIiJiKRRERMRSKIiIiKVQEBERS6EgIiLWLz7bQx6MP3BTAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYUAAAEGCAYAAACKB4k+AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAAIABJREFUeJzt3Xl4lPW9///nPWsyyWTfF8Imi8hWEUhdUCSAoi0oqD3+ToVqse1xwa2t9fRIrVovSzmntb/+Wr6e2tqe9rRiQQXZQbFfERBlkUUWWZKQTPZlMvvc9++PCTcZCCFgJjPJvB/XxZXJZCbzTpjMaz67ommahhBCCAEYol2AEEKI2CGhIIQQQiehIIQQQiehIIQQQiehIIQQQmeKdgFfRm1ta7RLEEKIPic7237Br0lLQQghhE5CQQghhE5CQQghhE5CQQghhE5CQQghhE5CQQghhE5CQQghhE5CQQghhE5CQQgR89xuF7LLf++QUBBCxLTKygoefngh77yzItqlxAUJBSFETDt8+BCqqrJy5fJolxIXJBSEEDFNUZRolxBXJBSEEDFNxhJ6l4SCEEIInYSCECLGSUuhN0koCCGE0EkoCCGE0EkoCCFiWjCoRruEuCKhIISIaYFAINolxBUJBSFETAsGJRR6k4SCECKmBYPBaJcQVyQUhBAxTVVlTKE3SSgIIYTQSSgIIWKa7H3UuyQUhBAxzWAwRruEuCKhIISIaUajvEz1JvltCyFimslkinYJcUVCQQgR00wmc7RLiCsRDYU//OEPzJo1i9tuu43HH38cr9dLeXk58+bNY/r06SxatAifzweAz+dj0aJFlJWVMW/ePCoqKiJZmhCij5Bx5t4VsVBwOBy8/vrrvPnmm6xatYpgMMjq1atZsmQJ8+fPZ/369aSkpLB8eeiIvTfeeIOUlBQ2bNjA/PnzWbJkSaRKE0L0KZIKvSmiLYVgMIjH4yEQCODxeMjOzuajjz5ixowZAMyZM4dNmzYBsHnzZubMmQPAjBkz2LZtm5y4JIQQvSxiIzi5ubl861vf4qabbsJqtXLttdcyatQoUlJS9IGjvLw8HA4HEGpZ5Ofnh4oymbDb7TQ2NpKRkXHBx0hPt2EyyXQ1Ifozuz1Bv5ydbY9iJfEhYqHQ3NzMpk2b2LRpE3a7nUcffZStW7eed7szC1M6axVcbNFKY6OrZ4oVQsSs1laPfrm2tjWKlfQfXYVrxLqPPvzwQ4qKisjIyMBsNjN9+nQ+/fRTWlpa9K1wq6urycnJAUKthqqqKiC0VW5raytpaWmRKk+cw+ls5dChA9EuQwgRZRELhYKCAvbs2YPb7UbTNLZt28bQoUOZNGkS69atA2DFihVMnToVgKlTp7JixQoA1q1bx+TJk2V5ey/6/e+X8fLLz1NefirapQhxDhlb7E0RC4WxY8cyY8YM5syZw+23346qqtx999089dRTvPbaa5SVldHU1MS8efMAmDt3Lk1NTZSVlfHaa6/x5JNPRqo00Yndu3cBUF9fG+VKhDiXvDnsTRFdKvjII4/wyCOPhF1XXFysT0PtyGq18qtf/SqS5QghhLgIWdEshBBCJ6EgziFNdSHimYSCCKNpcsqVEPFMQkGEkfNwhYhvEgoijN/vj3YJQogoklAQYeSQdBFrZL1S75JQEGEkFISIbxIKIozBIE8JIeKZvAKIMBIKQsQ3eQUQYSQUhIhv8gogwhiNcki6EPFMQkGEMRhkpocQ8UxCQYRRFHlKCBHP5BVACCGETkJBnEMONBEinkkoiDDBoCxeEyKeSSiIMMFgINolCBFG06T12pskFEQY2eZCiPgmoSDCSCgIEd8kFEQYCQUh4puEgggj21yIWCNbZ/cueQUQYSQURKyRgebeJa8AIozJJHsfCRHPJBREGAkFIeKbhIIII/23QsQ3CQUhhBA6CQUhREyT1mvvklAQ55A/QCHimYSCOIdM/xOxRaak9i4JBSFETPP7fdEuIa5IKIgwcvKaiDUejyfaJcQVeQUQYTRN9j4SscXtdke7hLgioSDOIQPNIra4XG3RLiGuRDQUWlpaeOSRR5g5cya33HILn376KU1NTSxYsIDp06ezYMECmpubgdBg0vPPP09ZWRm33347+/fvj2Rp4oJkUE/EFrfbpV8OBoNRrCQ+RDQUXnjhBa6//nrWrl3LW2+9xZAhQ1i2bBmlpaWsX7+e0tJSli1bBsDWrVs5ceIE69ev56c//SmLFy+OZGnigqSlIGJLx+4jaTVEXsRCwel0snPnTubOnQuAxWIhJSWFTZs2MXv2bABmz57Nxo0bAfTrFUVh3LhxtLS0UFNTE6nyxAVJS0HElo5BIOMLkRex3c/Ky8vJyMjg6aef5tChQ4waNYpnnnmG+vp6cnJyAMjJyaGhoQEAh8NBXl6efv+8vDwcDod+286kp9swmYyR+hHiUmqqjexse7TLEELn83n1y1Yr8vyMsIiFQiAQ4MCBA/z4xz9m7NixPP/883pXUWc6W6ByseXtjY2uLr8uLl1Li4fa2tZolyGErtXp1C9XVzeQmirPzy+rq2CNWPdRXl4eeXl5jB07FoCZM2dy4MABMjMz9W6hmpoaMjIy9NtXV1fr96+uru6ylSAiQ6akiljTcZ1Cx0FnERkRC4Xs7Gzy8vL44osvANi2bRtDhgxh6tSprFy5EoCVK1dy8803A+jXa5rG7t27sdvtEgpRIQPNInaoqorPe7b7yNvhsoiMiJ6o8uMf/5gnn3wSv99PcXExP/vZz1BVlUWLFrF8+XLy8/P55S9/CcCUKVN4//33KSsrIzExkRdffDGSpYkLkoFmETt8vvAtLmR1c+RFNBRGjhzJP/7xj/Ou/+Mf/3jedYqi8Oyzz0ayHCFEH6O3DBRAk5ZCb5AVzSKM7H0kYonXG2oZGKzG9s8lFCJNXgFEGBloFrHkzHRUJcHY/rl0H0WahIIIEwjINgIidpwZQzjTUpAxhciTUBBhAgF/tEsQQufxhFYwGxJM7Z9LKESahIIIIxuOiViitxQSQy0F2eYi8iQURBhVlTEFETtcrtBiNYMt1FKQxWuRJ6EghIhZbW2hLS4MViOKyUBbm+ySGmkSCiLMxfabEqI3Odv3PVIsRhSzAadT9j2KNAkFEUZCQcSSMyFgsBhQrAZaWyUUIk1CQYSRUBCxpLW1BQAlwYTBasTv9+kL2kRkSCgIIWJWc3MzGBQUk6KvVThzhK+IDAkFEUZmH4lY0tLSHBpkVhR9VXNLi4RCJEkoiDCBQCDaJQgBhA7eamlpRmlvIZxpKUgoRJaEggjj9/sufiMheoHP58Xv92Owhl6mzoSCs8NJbKLnSSiIMLILpYgVHaejdvwo01Ijq9vnKbjdbqqrq8O2QRg6dGhEihLRI3vLiFhx5rmomJSwj/IcjaxuhcL//M//sGTJEtLS0vQpi4qisGnTpogWJ3pHx3EEaSmIWHHm1DXFaAj7eO5pbKJndSsUfv/737Nq1SoKCwsjXY+Igo5/ZDKmIGLFeUtmNK39ellLE0ndGlPIzs6WQOjHOrYU/H7ZOlvEBoMhNIaAGgqD9kzAYJCh0EjqVkvhq1/9Ki+//DKzZs3CarXq18uYQn+hRbsAIc5js9kAUAOhtTOaXw27XkRGt0Jh5cqVAKxdu1a/TsYUhBCRlJxsB0Dzhia3aL7Qx6Sk5KjVFA+6FQqbN2+OdB0iivRmOmA0Gru4pRC9JyEhgcTERHzuUPdm0BX6mJGRGc2y+r0uQ8Hn82GxWC542lFiYmJEihK9y2g820cr/bUilmRl5VBx+hSapqG2hUIhMzMrylX1b12Gwt13382KFSsYP348iqKgaWf7nhVF4eDBgxEvUERexyCQUBCxJDc3l/Lyk2ieIME2P4qikJOTG+2y+rUuQ2HFihUAHDp0qFeKEdGhKIZOLwsRbbm5+QAEnX5Up5/MzCzMZnOUq+rf5BVAnENmIonYkZcXCoVAoxfVE9Q/F5HTZUth8uTJnS4U0TQNRVHYtm1bxAoTvafj1iWydbaIJbm5eQD4HK6wz0XkdBkKb775Zm/VIaKoYyjI1tkilmRmZgMQqA/td5SVlR3NcuJCl6Egq5jjQ8dVzLKiWcSS1NRUDAaD3oJNT5fpqJHWrXUKF+pGku6j/sHnO7sJnux9JGKJwWAgKSlZP6vZbrdHuaL+r1uh0LEbyev18s4772AydXvXbRHjOu6MKrukiliTlJSkh4LNlhTlavq/bs0+Kiws1P8NHjyYRx99lO3bt0e6NtFLOrYUZFtiEWtMJnOHy/JmNNIua0pqeXk5lZWV3bptMBhk9uzZPPjgg/p9582bx/Tp01m0aJH+IuTz+Vi0aBFlZWXMmzePioqKyylNXAZpKYhYFr64UrbNjrRuhcLkyZMpLS2ltLSUSZMmMXv2bP7t3/6tWw/w+uuvM2TIEP3zJUuWMH/+fNavX09KSgrLly8H4I033iAlJYUNGzYwf/58lixZchk/jrgcHccRpKUgYk0wGOhwOdjFLUVP6FYovPnmmyxfvpzly5fz9ttvs2PHDu64446L3q+6upr33nuPuXPnAqH1DR999BEzZswAYM6cOfpOq5s3b2bOnDkAzJgxg23btoVtqyEiJ/w8BQkFEVs6zoiTNy2R160OutTUVGw2GwaDgcOHD/Pxxx9TVlaGxWLp8n4vvvgiTz31FG1tbQA0NjaSkpKi9wvm5eXhcDgAcDgc5OeHViuaTCbsdjuNjY1kZGRc8Punp9swmWRXzy8rMfHs00DVVLKzZYaHiB1ut0u/bLEgz88I61YofPOb3+TPf/4zbW1t3H///QwbNowPPviAl1566YL32bJlCxkZGVx11VVdDkqfmeraWavgYsfuNTa6uvy66J7m5rO/x2AgSG1taxSrEeIsVVX1N5UAp0/XUlQkz88vq6tg7VYoaJqGzWZj9erV3HXXXTz88MPcfvvtXd7nk08+YfPmzWzduhWv14vT6eSFF16gpaWFQCCAyWSiurqanJwcINRqqKqqIi8vj0AgQGtrK2lpaZfwY4qeIV12Ina0tTnDtl45MzVVRE63xhS8Xi8+n48PPviA0tLS0B0vssXyE088wdatW9m8eTNLly5l8uTJ/OIXv2DSpEmsW7cOCO3COnXqVACmTp2q78q6bt26Cy6YEz2v4+9ZdkkVsaSlJRQChuTQtNTm5uZolhMXuvUKcOuttzJ58mROnz7NV77yFWpra8POar4UTz31FK+99hplZWU0NTUxb948AObOnUtTUxNlZWW89tprPPnkk5f1/cWlC986W4JYxI6mpkYATOnWsM9F5HSr++ihhx7im9/8JsnJyRgMBmw2G6+88kq3H2TSpElMmjQJgOLiYn0aakdWq5Vf/epX3f6eoud0nPsth+yIWNLQUA+AKcOKr9xJY2NDlCvq/7q9PLCpqYm9e/eGzRPOzZUTkPqDjoP8mowpiBhSX18HgNFuRrEY9c9F5HQrFH7xi1/wxhtvMGTIEP2dpKIoTJkyJaLFid7RcSBPDcp5CiJ26KFgM2OwGamrq0VVVWnRRlC3QmHt2rVs3LiR5OTkSNcjokC2uRCxyuGoBgUMNhPGJDO+pjaamhrJyJAttCOlW3GbnZ0tgdCPdVwc5PV6ZCsBETMcjioMNhOKQcHYPgOpuroqylX1b91qKYwbN47HH3+cmTNnhs06ku6j/uHMND/FnITmb6O1tYW0tPQoVyXiXWtrC62trZjzbEBoXAGgqqqSK6+8Kpql9WvdCoV9+/YB8Kc//Um/TsYU+o8z0/yMCekE/KHmuYSCiLbTp0M7MZ8JA2NKaFudykrZQTmSugyFo0ePAvDss8/2SjEiOkLT/BQMCZnQWkFDQz0DBw6OdlkizlVUlANgSg2FgdFuBuXs9SIyugyFhQsXAucvaNI0DUVR9B1ORd/W2NiAYkrAYLa1fy4LhET0lZefBMDYHgqK0YAx2UxFxSmZgRRBXYbC5s2be6sOESWaptHU1IhiSkExJwKyalTEhvLyk2BQMNrP7sZsTLPiKXdSV1dLTo6sk4oEido45/F4CAQCKEYrijE0icDplF0oRXQFg0EqKspDi9Y6rLg/05V06tTJaJXW70koxLkzAaCYJBRE7KiursLv92NKC99j7UxX0pmuJdHzJBTinMsV2qteMVhQjKE/uI771wsRDadOnQDOhsAZZ0Li5MkTvVxR/JBQiHNOpxMAxWhBUQwoBrOEgoi6kyePA5zXUjBYjRgSTfrXRc+TUIhzra3t3UftXUcYLXKQiYi648e/AAVMaecf+WtMs9Dc3KTvoCp6loRCnDsz0+jMzCODKZGWluawTfKE6E1er5cvjh/DmGpBMZ3/EmXOSgDg8OFDvV1aXJBQiHNn3m0ZTKE1CorZhqqqMi1VRM3Bg/sJBgKYsxM7/bo5K3T93r2f9mZZcUNCIc7V1dUCYDAnhX08c70Qve2DD7YAYC3qfBNOY5oFY7KZjz/eoY+JiZ4joRDn6upqUQwmaJ95pEgoiCg6evQwu3d/gjHNoh/BeS5FUbAOshMIBHj77X/0coX9n4RCnGtoqEcx2fStTM5sdVFfL4N4one5XC5+97tfo6GRNKbr8xISBqVgTDazceNa9u3b00sVxgcJhTgWDAZxudpQTAn6dYoxdFkWsIne5HBU8bOfLaa+vo7EYWn6uMGFKCYDyRNzwKDw618vZdu2f/ZSpf2fhEIcc7vdACgGs36dYjS3f83V6X2E6EmaprFr106ee+7fqayswDo4hcSR3du23ZRmxT4phwBB/s//+Q1/+csf5eTAHtCt8xRE/6RPO1U6vDdovyxTUkUkqarKnj2fsmrVSo4fP4ZiVEiekI11gP2Svo8lP4nUG820flTDxo3r+Gj7h8yYfis33VSGzWaLUPX9m4RCHDu7I7p29kpN6+ymQvQIr9fDJ598zLtr3qGy/VwES4GNxJEZ+mZ3l8pot5B6UwHuz5to+6KFN9/8G++++zY33zyDKVOmkpmZ1ZM/Qr8noRDHjMbQf7+mdWgVtF82meSpIXqG2+1mz55P2bVrB3v3forf7wcFLMXJJA5Pw5RyeWHQkWIyYBuVQcKwNDzHmvEebWHVqpWsWrWSQYOGMGHCRK6+eqJst90N8pcfx7o6pOTcg5WEuBSNjQ0cOPAZu3bt5LPP9hAIBAAwJptJHJyGtcSOMdl8ke8S0rYvNBMuaXTXM5IADGYDthHpJA5NxVvuxFfZxvETxzh+/BhvvPFXBgwYyIQJExk9ehzFxQPkoJ5OSCjEsa7GDWRMQVyKpqZGDh06yOefH+DQoQM4HNX614wpZhIL07EUJoXOR7jENxy+ytAGjd0JhTMUk4GEQSkkDEpB9QbxVbXhq2zjVMVJTp06wT/+8XdstiSGDx/BiBFXMmLEKAoLiyQkkFCIa/pZCsYOzXfZPlt0Q0NDPUePHubQoVAIVFdX6V9TTAbMeTbM2QlY8mxhJ6dFg8FqJGFgCgkDU1B9QfzVLvy1Hjy1bj79dBeffroLgKSkZEaMGMnw4VcybNhwCguLMRqNUa09GiQU4pi+xYXp7JxwxWgBxUhtbU20yhIxJhAIUF5+kqNHD3Ps2BGOHD1MY0OD/nXFZMCcm4g5OxFzVgLGNGvYaWmxxGAxYh1g12c5BV1+/LUeArVu3HUedu3aya5dOwGwWq0MHjyUoUOHMWTIFQwZMpSkpM633uhPJBTi2IkTXwBgSMjQr1MUAwZrGpWVFfh8PiyW6L7LE73P5Wrj8OHPOXr0MEePHub48WOhweF2BqsRc74Nc2YCpqwETDEcAhdjtJkxlpihxI6maaiuQCgkGjwE6j0cPLifgwf367cvKCjUQ2L48JFkZ+f0u/E3CYU4tnv3JwAYbeFT9kxJ2fg89ezfv5fx4ydEozTRi1paWjhy5BCff36Qzz8/REXFKbQOU5ONqRasGfZQCGQkYEgy9bsXQghNrjAmmTEmmWFgqCWh+oIEGrwE6j34GzxU1VRx+nQlW7eGNu1LS0tn+PCRDBs2guHDR5KfX9DnfzcSCnGqtraGo0cPY7Rlh3UfAZjsxfjqD7Ft2z8lFPohj8fD3r27OXRoP4cPH+L06cqzXzQomDKtmLMSMJ0JAXP8Dr4aLEYseTYseaGFcJqqEWzx4a/3EKjz0FLXwvbtH7J9+4cA2O12hg0bwbBhIxk37itkZ+dEs/zLIqEQpzZuXAeAOW3weV8zJGRgsKaxa9dO6upqycrK7u3yRA/z+33s27eH7du3sXv3Lr07SDEZMOckYspKwJyViCndimKMvXe6WowsqlQMCqY0a+iY0CGpoS4npx9/nQd/nYe2Orc+LvHXv77O4MFDmTSplGuumUxaWve274g2RYuV3/ZlqK2VTdsuR3NzEz/4wSL8qpGkobehKOfPsPA3HcdTtZ0bb7yZb37z/ihUKXrCsWNHeO+9TezatROPJ7TXlTHZjKUoCXOeLebHAwLNPtz/rCErM4sGVzPWq9Mve+Vzb9DHJWrc+Crb8Ne6QQt1TQ0fPpLJk6/l2mtviPqspuzsC28nErGWQlVVFd///vepq6vDYDBw1113cd9999HU1MRjjz1GZWUlhYWF/Nd//RepqaHEfeGFF3j//fdJSEjgpZdeYtSoUZEqL669884KfD4f1rwJnQYCgCm1BEP9AbZu3cL06beSl5ffy1WKL2vHjm0sW/b/oqoqhkQTCVekYi1ODh1z2Uf6vb27GvnOg9+hrKyMDRs2sOz1/8Y0NXZXJevjEoPMoTUSngC+yja8FU59+u6BA5/x7W9/L+rBcCER6yw0Go388Ic/ZM2aNfztb3/jL3/5C0ePHmXZsmWUlpayfv16SktLWbZsGQBbt27lxIkTrF+/np/+9KcsXrw4UqXFtfLyU2zZshGDxd5p19EZimLAkj0GVVX5619fj5nmu+iejz76v6GzCYxg/2oeaTOLSRqdGWoZ9JFAUD0BMmyplJWVAVBWVkaGLRXVE4hyZd1nSDCRMCSV1CmFpM0sxpSZwI4d2/jtb18hGAxGu7xORSwUcnJy9Hf6ycnJDB48GIfDwaZNm5g9ezYAs2fPZuPGjQD69YqiMG7cOFpaWqipkbnyPSkYDPLHP76KpmlYc7+ConT932+yF2G05bBv3x527vyol6oUPWH58v9F0zRsV2VgybP1mSDoSAtq1NXVsWHDBgA2bNhAXV0dWrBvvkEx2szYJ+WCUWHXrh188cXRaJfUqV4ZaK6oqODgwYOMHTuW+vp6cnJCI/I5OTk0tC+CcTgc5OXl6ffJy8vD4XDot+1MeroNkyk2m2Cx6M9//jNffHEUU8oATMkX7w5SFIWEvAm4Tqzn9df/m2uuGdfl/4eIHQsWzGfp0qW4PmvAmGTGlJ3QJ4PB5/Px29/+luXLl1NXV4fP56OvboitugO07qyBoEZpaSmTJo2PyS6kiIdCW1sbjzzyCD/60Y9ITr7wasDOuicu9iRubJSDYLpr7dpV/P3vf0MxJ5GQ1/1ppgZrCpbc8biqdvKDHzzNk08+LTtN9gGjRl3NAw98l1df/f9o+WcVRrsZ60A71uJkDAl9a9Khz+fj9OnT0S7jsmiqhq/KhfdkK36HCzSYMGEiCxZ8l4aG6L1+RWWgGcDv9/PII49w++23M336dAAyMzOpqakhJyeHmpoaMjJCq2nz8vKorj67iVZ1dbW8K+0BTqeTFSveYMuWDSimRBKLbwjf66idx7EbgITcced9zZw6GM3voq5uPy++uJj587/N2LHj++Q7z3hSWnodmZlZbNq0nk8+/RjXvgZcnzVgzrNhHWDHkpOIEsdrECJF0zQCjV58FW34yp2o3tDYwcCBg7n++hu54YabYrKFcEbEQkHTNJ555hkGDx7MggUL9OunTp3KypUrWbhwIStXruTmm2/Wr//zn//MrFmz2LNnD3a7XULhS3C7Xaxfv4Z1697F43FjsNhJHHAjBnNSp7cPtJ4KXegkFBRFwZo9GsVopcXxCb/61RIGDx7KnXfezciRMkMsloUWUo3A6Wzlo48+5J//fI9Tp07ir3KBQcGcmYA5LxFLng1D8qXvYCpCVF8wNA212kXA4daDIDk5mdIbrue666ZQXDwgylV2T8TWKXz88cfce++9DBs2TN+O9vHHH2fMmDEsWrSIqqoq8vPz+eUvf0laWhqapvHcc8/xwQcfkJiYyIsvvsjo0aO7fAxZpxCupaWFfft2t//bg9vtRjFasWSOxJw+FMVw4fcAzqNvA5A89GtdPkbQ04Sv7jMCrRUAFBUVM2bMeMaMGceQIVfE9DsgEXLy5Al27drBvn27OXnyhH69IcmEJc+GOTe0w6lijG4rItjmp2ld+XnXp80oDm1FEUWa1r6yubo9CBo8+gGGqalpjBkzjrFjxzNmzPiYPLCqq+4jWbzWh3m9HsrLT7F//z727t3NiRNf6GMzitmGOW0IlvRhKMaL/wF1NxTOCLob8NXtJ9BWpZ/WZrMlcdVVYxgzZhxDhw4jKytb9qePcU1Njezbt4e9e3ezf/9ePB4PAIpRwZSdiCU3EXOeLSovwqonQOO7p867Pv3WAVEZF9H8Kv7aUAj4HW5Ud2hqrKIoDB48VH9zNGBAScy3uCQU+jhN06ivr6O8/BTl5SepqDhFefkpamocZwfoFQVjYjam5HyMyQUYLCmX9MS81FDQa1MDBNscBJxVBNpOo/nPDp4lJCRQVDSA4uIBFBeXUFw8gKKiYqzWhEt6DNE7AoEAR458rofE6dMV+teMdjPmPBuWfBumzN6bydS4vhzV2WGH1mQz6dOLe+WxIdRa8Z1uw1/txl/vATX095aUlMzo0WMZPXosV101Brs9pddq6gkSCn1EIBCgrq6WmppqampqcDiqQkFQcQq3K3ymgmK0YLCmYbCmYbRlYUrK63QAubsuNxQ60jQN1ddC0FlF0NOI6m1C9bagt6sJvavKycmlqGgAhYVF5OTk6v/s9ksLMhFZdXW17Nu3h337dnPgwGf4fD4ADAlGLEVJWIqSQ3slRfD/LNDso3lzBWihQLBPyo34NhdBdwBfhRNfRRuBRq9+fUnJIMaMGceYMeMYNGhIn24FSyjEEI/HQ02Ng9paBzWBpG2fAAAV1klEQVQ1Hf7V1tBQX9f51FyLHaM1DUNCmv5RMfXsgqSeCIXOaGoQ1duM6m0i6GlqD4omtKDvvNtarQnk5uaSnZ0bFhbZ2TlkZGT26T/Cvs7v93Ho0EE+/ng7u3btxOUKncxnsJmwFCWRUGKP2AlrjWtDW3ln3FISke8Poa4hb7kTb7mTQH17F5qicOWVV3HNNZMZO3Y8qalpEXv83iah0ItUVaWhoZ66ulpqa2uora2hrq62vQXgoKWludP7KaZEDOZkFEsyBksyBnP7R2tqlwPEPSVSodAZTdPQAi5Ubyuq34nqa0XzOdsvO0E7f/m/0WgiOzub7OwcsrJyzrtss3U+q0r0vEAgwP79+9ixYxuffvqxPg5hzreROCwNc2bPdg82rg2NK6TP7PnZO6o7gPtYC97jLWh+FUVRuOKK4UyaVMrVV08kJSW1xx8zFkRtnUJ/5XK14XBUt7/o11JXF3rxr62rpaG+7gJ7migoZhvGpFwMZjsGS3sAtL/498YLf6xQFAXFnNTp9NhQYHhQ/e1B0SEsHLX1YWcBd2SzJZGdnd0eEjnnXM6RWVE9yGQyMXbseMaOHY/P52P37l2sW/du6IS2KhemDCuJI9L1MwhiUbDNj/tQE95yJ6gadnsKN8+azvXX30h6esbFv0E/Ji2FLrjdbk6fruT06QoqK8uprKygsrKCpqbGTm+vmBL0F7vQu/7QR4M5CcVsu+heQ9HkPPo2mqZhv+Lr0S6lS1rQ3x4SbWh+J6q/DdXnRPO3ofrbLtjKyM8voKioiIKCIgoLiygsLJbZUT1I0zQOHz7E2rWr2LPnUwAshUkkjc380jOFerKloGkanqPNuA80ogU1cnPzmDFjFl/96vVxdfSsdB91g6qqfPbZHj7//JAeAPX1defdTjHbMFhSMVjtZ1/wLe0f++i7/aCniUDlFrKyMqlvcWPMnoQxoe/1n55pZYQC4kxgtKJ6W1B9zaCGB4bZbKGgoJDCwiKKioqZOLGUjIzMKFXff1RUlPP66//N0aOHUSxGksZmYi2+/APveyoUgq0+nLtqCTR4SU5O5hvf+CaTJn01Lt8YSCh0IRAIsH37h6xZ807YsYSKKaH9xT/0z2hNxWBN+VIzfGKVr3wdD37rX8/uWf/7P2EunhHtsnqUpmmhsPA2E/Q2tw9+N6P6WvR1FgaDgdLS65g58zYKC4uiXHHfpqoqmzdvYPnyv+Lz+UgcmU7iiLTLmhzRE6Hgb/DQ+qEDzRdk4sRS/uVf7iMlpW9NI+1JEgoXcOzYEX7zm1/R2FgPioIppQRz6iCM1jQUk7WHqoxtasBNattOfve73+nXPfjggzQnXXPe2c39kaapaD4nAVct/obPQyEBTJ78VR544Htx+S6yJ1VXV7F06UvU1dViHZxC0tjMSw6GLxsKPocL50c1KBrcd98DXH/9jZf1ffqTrkIhrp/x1dVVoUAAFHMypqR8jLbsuAkEANRgp3vWn9vV0l8pigGDNQVTch7G5LNbtx86dDBmD0HpS/Ly8vnRjxZTWFiM94sWXPsbLvl7WAqTsBRe3uwyf70H50cOjAYjDz30mARCN8R1SwHg+PEvWLt2FR9/vB1N01AMZgwJaRis6RgT0jAkpIe6jS5wbGVfp/qctB1bhcViISsrS9+zPmnIbRgsl98PHMvUgAfV00TQ24jqaUT1NKH6WgGN1LR0Zky/hSlTppKYGLuzZ/oap7OVF154FoejmqRxWSQMjnzXTdDpp+X90+DXePTRpxg9emzEH7OvkO6jbqipcbBhwxr2H/gMR3VV+CIyxYDBkoIhIR1jQro+zqAY+87RhhdyJhTO1R9CQdOCoSmt3hZUTyNBbxOqpxEt4A67XUJCAgMGDOS666YwefK1MbmBWX9QU+Pg+Rf+A6ezlZTr8jFnR657UvWrtLxXSbDVz333PcCUKVMj9lh9kYTCJfJ6PVRUlHPq1ElOnTrBqVOh/Yb8fn/Y7RSjBcWSgtFiDwWFJSXUqjAn9Zmw6A+hoKn+0EI4X3MoALwtqL4WVL8Tznl6p6dnMGBACcXFJZSUDKS4uESmpvaiI0c+5+WXn0czQspNBRHZaE/TNFo/cuCvclFWdgvf+Ma/9vhj9HUSCj0gGAzicFRz6tQJKivLOX36NFVVldTUOFBVNfzGihGDxY7BmhLam6i9O0oxxd6RiH0pFDQt2P6uv73rpz0AtMD5J1gl2mwUFhSRn19Afn4hxcUDGDCgpM9tXNYfbdmykT/96fcYUy2k3ljQ41t0uw424j7YyIgRo3jiiR/KwsVOyIrmHmA0GikoKKSgoDDs+kAggMNRTVVVKCSqqirbA+M0/pYm4OzWv4oxIbR/UXtIGBLSQ6uZY3hRW7RoQV97d09TaHM9T2PY9NEz0tLSyc8fREFBIfn5heTnF1BQUEhKSmrMBbAIufHGmzl58jhbt27B+UkdyROye+z/ylfVhvtgI5mZWXz3uw9LIFwGCYUvyWQyta+QDZ/Xrqoq9fV1VFScCuuGqq+vJth29thRFCPGxMzQltdJ+aGxijh8MdOCfoKuGgLOKoKu6tAeSB2YzWZKBoa6ewYMGMiAASUUFBRhs8lgcF+jKAr33jufiopTfPHFMTzpVhKHfvk9hoKtPpwf12Iym3noocelVXiZpPuol7W1OSkvDwVFeflJTp48TkXF2dOlFFMixqQ8TMn5mJLyu3VAzpehBty0HXnrvOuTrvh6xNcpBD1NBNqqQlttu+v0VkBCQiJDhgxtD4BQ/39eXr686+tnGhsb+MlPfkRLa8uXHnjW/CrN750m2Orj29/+HqWl1/Vgpf2PjCnEuObmZg4c2Me+fXv47LO9OJ2hn0sxWjCnD8OSMTyi4eA8thrNd/Z3abDYSRoyK2KPF3TX463dF9ZiGjhwMFddNYarrhrD4MFDZQZQnDh8+BAvv/w8mBVSpxZiSLz0/3dN03DurMFX0ca0aTP4l3+5LwKV9i8SCn2IqqqcPHmCPXs+YdOm9bS1OUPhkDECS+aIiIw/BD1NuI6vAzQMFjsJhddGZO8j1duCx/EpwbbQTqcjRozi+uunMGrU6H67RbG4uPXr1/C///snTFkJpFyXj2K4tO5Tz7Fm2vbUM3ToFXz/+z+WNxTdIKHQR7ndbjZvXs+aNatwudow2YtJKJiMYuj5bpRI75IadNfjLn8fLehj+PCRzJ49l+HDR0bksUTfomkav/nNL9m1aweJI9OxjUzv9n0DzT6at1SSbEviJz95Ke63ve4umX3URyUmJjJr1te58cabeeWVpRw+fAh3RYDE4usissI6UgPcAVctnvL3QQuyYMFC2WpAhFEUhfnzH+CLL47SeKgBS24ipoyLH9SjBTWcH9eAqvGtb31HAqGHyFzIPiApKZnHH/8ho0ePJdhWhadqZ6fHdsYi1duCp+IDFFS+971FEgiiU0lJydx//3dAA+cndWjqxZ/f7iNNBJt93HDDTYwb95VeqDI+SCj0ERaLhe99bxGDBg0h0HwCr+MTtHPm7MeaoLcFd/l7aEEfCxYs5Oqrr4l2SSKGXXnlVVx//Y0EW3x4vmjp8rbBNj+ez5tISUnlrrvu7aUK44OEQh9itVp59NEnKSgowt94BE/lNjQ1EO2yOhVw1eI+uRHV72Lu3Hu49tobol2S6APuvPMebDYb7oONqP4Lv+lxtZ+cdvfd98palR4modDHpKSk8qMfPcuwYSMItJbjOr6OgKsm2mXpNDWIt2YP7pObUbQACxYs5NZbvxbtskQfkZKSwi23fA3Nr+I52tzpbYKtPnwVToqLS5g8+dperrD/k1Dog2y2JJ544odMn34Lmt+J++RmPFUfowY8Ua0r4KzGdXwtvvqDZGVl8cQTT8sYgrhkU6eWkZSUjPdYC1rw/NaC+0gzaPC1r90Rl6v/I01mH/VRZrOFe+75V665ZjK///3vqKo6SqDlJObMEaHFbpd4XrTJfvlHHQbdDXhr9xBsc6AoCtOmzeCOO+4mIeHiM0iEOFdiYiI33HATa9a8g6+yDeuAs9MnVb+Kr6KNzMwsxo+/OopV9l+yTqEfCAQCvPfeJt5++x84na0opgQsmaMwpw2OyJqGM1RvC966zwi0hDb9GzVqNPPmfYMBAwZG7DFFfKipcfDDHz6GOTuRlOvz9es9J1po+6SOOXPu4vbbZ0exwr5N1in0cyaTiWnTZnDttdezZs0q1q9fg9exC1/DQSxZozCnDurRldCqz4m3bj+B5hOAxoCSgcyb+w1GjRrdY48h4ltOTi6DBg3h+IljqN4gBmvozY2vsg2ASZNKo1levyah0I8kJtq44467mDZtBu+++w6bN6/HW7UTf/3nWHPGYUzO/1J9sFrQh7duP/7GI6CpFBQUMWfOPL7ylQnStyt63IQJEzl+/Bj+ahfWEjtaQMVf66G4uIScnNxol9dvSSj0Qykpqdxzz//DjBm38tZbb/LBB+/hrtiK0ZaDNe9qjNZL22dI01T8jUfx1X2GFvSRmZnFHXfcxaRJX5UTy0TEXHXVWN5446/4at1YS+z46zyganLWcoRJKPRj6ekZzJ//baZNm8kbb/yFffv24Dq+DkvWaCyZw7vVpaT6WvGc3k7QXUdCQiK33/ENpk2bgdls6YWfQMSzwsIi7HY7bbWhM7X9daGPI0eOimZZ/V5Mvc3bunUrM2bMoKysjGXLlkW7nH6jqKiYxx77AQ8//AQpdju+2j24Tm5CPecA+3P5m4/jOr6WoLuOCRMm8tJLS7nlltslEESvMBgMDBkyDNUdIOgOEKj3oigKgwcPjXZp/VrMhEIwGOS5557j1VdfZfXq1axatYqjR49Gu6x+Zfz4q3n++Z8zcWIpqrse94mNBL3nbyegaRreuv14Tm8nwWrlO995hO99b5Fsby163ZAhoQAINHgJNnkpKCgkMTGyhz/Fu5gJhb1791JSUkJxcTEWi4VZs2axadOmaJfV7yQnJ/Pggw8xe/ZcVH8b7pObUP1tYbfx1e3HV7uPjMwsnnnmJ0ycODlK1Yp4V1xcAoDvdBtaUJPpzr0gZsYUHA4HeXl5+ue5ubns3bu3y/ukp9swmeSIxstx//33kZOTwbJly3BX/F9sJTejGIwEnKfx1X1GdnY2P//5z8nMzIx2qSKOjR0bOnPDVxE6s3v48KFdzrEXX17MhEJna+guNs2xsdEVqXLiwqRJUzhw4HP++c/38TV8jiVjOJ6qnZhMJr773UdRVYssEBRRpWkWLBYLPp8PALs9Q56TPaCrYI2Z7qO8vDyqq8+e2etwOMjJyYliRf2foijcc8+/kphow9/wOb7Gw2gBN9OmzWTgwMHRLk8IFEUhJ+dsD0LHyyIyYiYURo8ezYkTJygvL8fn87F69WqmTp0a7bL6PZvNxs03T0cLevHV7MFgMDJz5qxolyWErmMXZkaGdGdGWsyEgslk4j/+4z944IEHuPXWW7nlllu44oorol1WXBg/foJ++YorhsksIxFTOh6zKTOPIi9mxhQApkyZwpQpU6JdRtwpKRmoXx46dFj0ChGiE8nJMrDcm2KmpSCix2AwkJKSAkBBQWGUqxEinN0uodCbYqqlIKJn0aLvc+TIYSZMmBjtUoQIYzKZo11CXJFQEAAMHDhYZhwJIaT7SAgR22Rb9t4loSCEiGn5+QUAXHvtDVGuJD7IcZxCiJimaRonThynoKAAq1XO/e4JchynEKLPUhSFQYNkvKu3SPeREEIInYSCEEIInYSCEEIInYSCEEIInYSCEEIInYSCEEIInYSCEEIIXZ9evCaEEKJnSUtBCCGETkJBCCGETkJBCCGETkJBCCGETkJBCCGETkJBCCGETkJBCCGETkJBsHXrVmbMmEFZWRnLli2LdjlC6J5++mlKS0u57bbbol1K3JBQiHPBYJDnnnuOV199ldWrV7Nq1SqOHj0a7bKEAOCOO+7g1VdfjXYZcUVCIc7t3buXkpISiouLsVgszJo1i02bNkW7LCEAuOaaa0hNTY12GXFFQiHOORwO8vLy9M9zc3NxOBxRrEgIEU0SCnGus62vFEWJQiVCiFggoRDn8vLyqK6u1j93OBzk5OREsSIhRDRJKMS50aNHc+LECcrLy/H5fKxevZqpU6dGuywhRJTI1tmC999/nxdffJFgMMidd97Jd7/73WiXJAQAjz/+ODt27KCxsZHMzEwefvhh5s2bF+2y+jUJBSGEEDrpPhJCCKGTUBBCCKGTUBBCCKGTUBBCCKGTUBBCCKEzRbsAIaLF5/OxdOlSNm7ciMlkIiEhgYceeohp06Z1eb/t27fj9/u57rrreqlSIXqPhIKIW4sXL8blcrF69WqsViuHDx/mgQceIDU1lWuuueaC99uxYwcul0tCQfRLsk5BxKXKykpuu+02tmzZQlpamn79X/7yF9atW8eECRNwuVz84Ac/AOCVV17B5XIxe/ZsvvWtb6GqKjk5OcyaNYuFCxeyZcsWXnnlFQKBAAaDgZdeeokRI0awdetWli5dSjAYJCMjg+eee46SkhK2b9/OCy+8wJgxY9izZw8mk4mXX36ZX//61xw5coT8/HxeeeUVbDYbPp+P//zP/2Tnzp34/X6GDRvG4sWLSUpKitavT/RjMqYg4tLhw4cZMGBAWCAAjBs3jkOHDl3wfsOHD+eee+5h9uzZvPXWWyxcuJDjx4/z7//+7yxdupS3336bv//97xQVFVFfX8/3v/99lixZwjvvvMNtt93Gk08+qX+vY8eOce+99/LOO+8wbtw47r//fp5++mneffddDAYDq1evBuDVV1/FbrezfPly3nrrLXJycuQwJBEx0n0k4lJPNpA//PBDbrjhBgYOHAiAxWLBYrGwY8cORowYwdChQwG48847+clPfoLT6QRg0KBBjBw5EoArr7yS06dP69uYjxo1ipMnTwKwefNmnE4n69atA0JjISNGjOix+oXoSEJBxKVhw4Zx6tQpmpqawloLu3fvZvjw4RiNRlRV1a/3er0X/F4XChhN07rchtxiseiXjUYjVqs17PMzj6lpGs8++yylpaUX/8GE+JKk+0jEpaKiImbOnMnixYv1F9/Dhw/z29/+loceeogBAwawf/9+VFXF6XTy3nvv6fdNTk6mtbVV//y6665j69atnDhxAgi9k3c6nYwfP56DBw9y7NgxAFasWMGVV15JcnLyJdU6depU/vCHP+DxeABwOp369xSip0lLQcStxYsX84tf/IJbb70Vs9mM1WrlmWeeYeLEifh8PtasWcOsWbMoKSlh1KhR+v2mTZvGW2+9xde//nV9oPmnP/0pjz32GMFgEKPRyEsvvcTw4cN5+eWXefLJJwkEAmRkZPDzn//8kutcuHAhv/71r5k7dy6KoqAoCg899BBDhgzpyV+HEIDMPhJCCNGBdB8JIYTQSSgIIYTQSSgIIYTQSSgIIYTQSSgIIYTQSSgIIYTQSSgIIYTQ/f9yjfTfpuCpfQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for name in trainFilled.columns:\n",
    "    if name != 'Outcome':\n",
    "        fig=plt.figure()\n",
    "        sns.violinplot(x='Outcome', y=name, data=trainFilled)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "通过violin 图我们可以发现 怀孕次数多可能导致糖药病的几率大一些，Glucose 不是糖药病的比是糖药病的人的均值和分布情况都低很多。skinThickness Insulin BMI是糖药病的人都比不是糖药病的普遍要高一些。 年轻人得糖药病的几率要小一些。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  4.4 相关性分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 936x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cols=trainFilled.columns\n",
    "data_corr=trainFilled.corr().abs()\n",
    "plt.figure(figsize=(13,9))\n",
    "sns.heatmap(data_corr,annot=True)\n",
    "sns.heatmap(data_corr,mask=data_corr<1,cbar=False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SkinThickness and BMI =0.57\n",
      "Pregnancies and Age =0.54\n"
     ]
    }
   ],
   "source": [
    "size = data_corr.shape[1]\n",
    "corr_list = []\n",
    "for i in range(0,size):\n",
    "    for j in range(i+1,size):\n",
    "        if (data_corr.iloc[i,j]>0.5 and data_corr.iloc[i,j]<1):\n",
    "            corr_list.append([data_corr.iloc[i,j],i,j])\n",
    "            \n",
    "s_corr_list = sorted(corr_list, key=lambda x: -abs(x[0]))\n",
    "for v,i,j in s_corr_list:\n",
    "    print('%s and %s =%0.2f' % (cols[i],cols[j],v))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5 数据预处理"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.1 分离目标值和特征值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "Y_train = trainFilled['Outcome']\n",
    "X_train = trainFilled.drop([\"Outcome\"], axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.2 标准化数值并且分离测试值和训练值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jack/anaconda3/lib/python3.6/site-packages/sklearn/cross_validation.py:41: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. Also note that the interface of the new CV iterators are different from that of this module. This module will be removed in 0.20.\n",
      "  \"This module will be removed in 0.20.\", DeprecationWarning)\n"
     ]
    }
   ],
   "source": [
    "# 数据标准化\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "# 采用sklearn的分割函数\n",
    "from sklearn.cross_validation import train_test_split\n",
    "\n",
    "# 初始化特征的标准化器\n",
    "ss_X = StandardScaler()\n",
    "\n",
    "# 分别对训练和测试数据的特征进行标准化处理\n",
    "X_train = ss_X.fit_transform(X_train)\n",
    "\n",
    "# 分割比率20%\n",
    "x_train, x_test, y_train, y_test = train_test_split(X_train, Y_train, test_size=0.20, random_state=0) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6 Logistic 模型训练及评估"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6.1 通过gridSearchCV 寻找最佳参数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "\n",
    "#需要调优的参数\n",
    "# 请尝试将L1正则和L2正则分开，并配合合适的优化求解算法（slover）\n",
    "tuned_parameters={'penalty':['l1','l2'],'C':[0.01,0.03,0.05,0.07,0.1,0.3,0.5,0.7,1,3,5,7,10,20,50,70,100], 'solver':['liblinear'],'multi_class':['ovr']}  \n",
    "\n",
    "lr_penalty= LogisticRegression(tol=1e-6,class_weight=\"balanced\",random_state = 20)\n",
    "grid= GridSearchCV(lr_penalty, tuned_parameters,cv=5, scoring='neg_log_loss')\n",
    "grid.fit(x_train,y_train.ravel())\n",
    "\n",
    "# 获得预测值\n",
    "lr_predict_test =grid.predict(x_test)\n",
    "lr_predict_train = grid.predict(x_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由于数据集比较小，此次采用GridSearchCV进行调参， 由于是不是糖药病的样本不均衡，采用class_weight = 'balanced'选项。 评分选择了 neg logloss，采用一般的五则交叉验证进行训练模型。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6.2 查看训练出的评分和准确率"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "9\n",
      "{'C': 0.1, 'multi_class': 'ovr', 'penalty': 'l2', 'solver': 'liblinear'}\n",
      "LogisticRegression(C=0.1, class_weight='balanced', dual=False,\n",
      "          fit_intercept=True, intercept_scaling=1, max_iter=100,\n",
      "          multi_class='ovr', n_jobs=1, penalty='l2', random_state=20,\n",
      "          solver='liblinear', tol=1e-06, verbose=0, warm_start=False)\n",
      "0.47101711535166246\n"
     ]
    }
   ],
   "source": [
    "print(grid.best_index_)\n",
    "print(grid.best_params_)\n",
    "print(grid.best_estimator_) \n",
    "print(-grid.best_score_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "best params for logistic regression:  {'C': 0.1, 'multi_class': 'ovr', 'penalty': 'l2', 'solver': 'liblinear'}\n",
      "best neg lose for logistic regression:  0.47101711535166246\n",
      "confusion matrix:\n",
      "[[46  7]\n",
      " [23 78]]\n",
      "regression report:\n",
      "             precision    recall  f1-score   support\n",
      "\n",
      "          1    0.66667   0.86792   0.75410        53\n",
      "          0    0.91765   0.77228   0.83871       101\n",
      "\n",
      "avg / total    0.83127   0.80519   0.80959       154\n",
      "\n",
      "accuracy score for train data: 0.81596\n",
      "accuracy score for test data: 0.80519\n"
     ]
    }
   ],
   "source": [
    "print(\"best params for logistic regression: \",grid.best_params_)\n",
    "print(\"best neg lose for logistic regression: \",-grid.best_score_)\n",
    "print(\"confusion matrix:\")\n",
    "print(metrics.confusion_matrix(y_test, lr_predict_test, labels=[1, 0]) )\n",
    "print(\"regression report:\")\n",
    "print(metrics.classification_report(y_test, lr_predict_test, labels=[1,0], digits=5))\n",
    "print(\"accuracy score for train data: {0:.5f}\".format(metrics.accuracy_score(y_train, lr_predict_train)))\n",
    "print(\"accuracy score for test data: {0:.5f}\".format(metrics.accuracy_score(y_test, lr_predict_test)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "找到最优解C值为0.1，正则项为 L2,准确率在训练集上面的0.82 在测试集上面的准确率为 0.77, nll -0.464"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jack/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:122: FutureWarning: You are accessing a training score ('mean_train_score'), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True\n",
      "  warnings.warn(*warn_args, **warn_kwargs)\n",
      "/home/jack/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:122: FutureWarning: You are accessing a training score ('std_train_score'), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True\n",
      "  warnings.warn(*warn_args, **warn_kwargs)\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot CV误差曲线\n",
    "test_means = grid.cv_results_[ 'mean_test_score' ]\n",
    "test_stds = grid.cv_results_[ 'std_test_score' ]\n",
    "train_means = grid.cv_results_[ 'mean_train_score' ]\n",
    "train_stds = grid.cv_results_[ 'std_train_score' ]\n",
    "\n",
    "\n",
    "# plot results\n",
    "n_Cs = len(tuned_parameters['C'])\n",
    "number_penaltys = len(tuned_parameters['penalty'])\n",
    "test_scores = np.array(test_means).reshape(n_Cs,number_penaltys)\n",
    "train_scores = np.array(train_means).reshape(n_Cs,number_penaltys)\n",
    "test_stds = np.array(test_stds).reshape(n_Cs,number_penaltys)\n",
    "train_stds = np.array(train_stds).reshape(n_Cs,number_penaltys)\n",
    "x_axis = np.log10(tuned_parameters['C'])\n",
    "\n",
    "for i, value in enumerate(tuned_parameters['penalty']):\n",
    "    plt.errorbar(x_axis, -test_scores[:,i] ,label = tuned_parameters['penalty'][i] +' Test')\n",
    "    plt.errorbar(x_axis, -train_scores[:,i],label = tuned_parameters['penalty'][i] +' Train')\n",
    "\n",
    "plt.legend()\n",
    "plt.xlabel( 'log(C)' )                                                                                                      \n",
    "plt.ylabel( 'neg-logloss' )\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x_axis, -test_scores[:,1], 'b-')\n",
    "plt.xlabel( 'log(C)' )                                                                                                      \n",
    "plt.ylabel( 'neg-logloss' )\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "根据C的取值 测试集的变化可以看出在 log(c) = -1 左右取值最小"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7 线性SVM"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 7.1 模型训练及最优值寻找"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 载入库包\n",
    "from sklearn.svm import LinearSVC\n",
    "\n",
    "tuned_parameters_svc= {'penalty':['l2'],'C':[0.001,0.01,0.05,0.1,0.5,1,1.5,5,10,50,100,200,500,1000,5000,10000],'loss':['hinge']}\n",
    "grid_svc=GridSearchCV(LinearSVC(tol=1e-7,class_weight=\"balanced\", random_state=42),tuned_parameters_svc) \n",
    "grid_svc.fit(x_train,y_train)\n",
    "svc_predict_test =grid_svc.predict(x_test)\n",
    "svc_predict_train =grid_svc.predict(x_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 7.2 结果评分及曲线图绘制"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "best params for Linear SVC:  {'C': 0.5, 'loss': 'hinge', 'penalty': 'l2'}\n",
      "best score for Linear SVC:  0.8452768729641694\n",
      "confusion matrix:\n",
      "[[43 10]\n",
      " [19 82]]\n",
      "regression report:\n",
      "             precision    recall  f1-score   support\n",
      "\n",
      "          1    0.69355   0.81132   0.74783        53\n",
      "          0    0.89130   0.81188   0.84974       101\n",
      "\n",
      "avg / total    0.82325   0.81169   0.81467       154\n",
      "\n",
      "accuracy score for train data: 0.85016\n",
      "accuracy score for test data: 0.81169\n"
     ]
    }
   ],
   "source": [
    "print(\"best params for Linear SVC: \",grid_svc.best_params_)\n",
    "print(\"best score for Linear SVC: \",grid_svc.best_score_)\n",
    "print(\"confusion matrix:\")\n",
    "print(metrics.confusion_matrix(y_test, svc_predict_test, labels=[1, 0]) )\n",
    "print(\"regression report:\")\n",
    "print(metrics.classification_report(y_test, svc_predict_test, labels=[1,0], digits=5))\n",
    "print(\"accuracy score for train data: {0:.5f}\".format(metrics.accuracy_score(y_train, svc_predict_train)))\n",
    "print(\"accuracy score for test data: {0:.5f}\".format(metrics.accuracy_score(y_test, svc_predict_test)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jack/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:122: FutureWarning: You are accessing a training score ('mean_train_score'), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True\n",
      "  warnings.warn(*warn_args, **warn_kwargs)\n",
      "/home/jack/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:122: FutureWarning: You are accessing a training score ('std_train_score'), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True\n",
      "  warnings.warn(*warn_args, **warn_kwargs)\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAEGCAYAAAB/+QKOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAAIABJREFUeJzs3XlY1Oe5+P/3LAzMsA4wMyCyqOAKKlHjlohijEFi1Gja0yxdNPWc5Nja32mP8Ury9bSepidN06uXzenxNE1D2vht8m2SNmnFZnHDfV9GxQVQZB+2AWZYZv/9MTCKbIMw4ODzui6vwHw+z3DPlM7Ns92PxOVyuRAEQRCEO0iHOwBBEATh3iQShCAIgtAtkSAEQRCEbokEIQiCIHRLJAhBEAShW/LhDmCw1NSYBtRerVZhNLYMUjS+5U+xgn/F60+xgn/F60+xgn/FO5BYNZrQHq+JHkQ7uVw23CF4zZ9iBf+K159iBf+K159iBf+K11ex+jRBHDhwgKVLl7JkyRLefvvtLtcrKip47rnnWLlyJcuXLycvLw+AsrIypk6dyooVK1ixYgVbtmzxZZiCIAhCN3w2xORwONi6dSs5OTnodDrWrFlDZmYmycnJnnu2b99OVlYWTz/9NIWFhaxfv569e/cCkJCQwGeffear8ARBEIQ++KwHodfrSUxMJD4+HoVCQXZ2Nnv27Ol0j0QiwWw2A2AymdBqtb4KRxAEQegnn/UgDAYDMTExnu91Oh16vb7TPRs2bGDdunXs2LGD1tZWcnJyPNfKyspYuXIlISEh/OAHP2DmzJm9/jy1WjXgcbjeJmvuNf4UK/hXvP4UK/hXvP4UK/hXvL6I1WcJorsSTxKJpNP3ubm5rFq1irVr13L27Fk2bdrEzp070Wq17Nu3D7VazcWLF/nXf/1XcnNzCQkJ6fHnDXS1gUYTOuCVUEPFn2IF/4rXn2IF/4rXn2IF/4p3ILEOyyqmmJgYqqqqPN8bDIYuQ0gff/wxWVlZAKSnp2OxWDAajSgUCtRqNQCpqakkJCRw48YNX4UqCIIgdMNnCSItLY3i4mJKS0uxWq3k5uaSmZnZ6Z7Y2FiOHj0KQFFRERaLhcjISOrr63E4HACUlpZSXFxMfHy8r0IVBEEQuuGzISa5XM6WLVt4/vnncTgcrF69mpSUFLZt20ZqaiqLFy9m8+bNvPrqq7z33ntIJBJef/11JBIJJ0+e5Ne//jUymQyZTMZPfvITIiIifBWqIAwLl8tFbWs9V40FlJsrSQyLJzVqEiGK4OEOTRAAkIyU8yAGOlZ4v4w3Dgd/itfXsTZZTVyrL+SqsZArxkLq24ydrkuQMDY8iamayaRFT0an0gxrvIPJn2KF/se7ZMnDfPXVQQoKrvLmm6/T3NyMTCblm99cy+LFj3a695e//DkXLpzHbrdRUVFBQkIiAN/61loWLXrE65959eoVjMZ6li9f6pM5iBFTakMQOphtzRwpP0GDtRGtUoNOpUGr0qAOCkcqGdriAW32NgobbrgTQn0BFc235uVUciXTNalMUKcwOjSWooZi9LX5XG8spqjxBn8tzEWn0jA1egpp0ZMZE57g8/htDhst9lb3P1srLfaW9v+6/7W2fz0xMoUHYx7waSz+KjAwiFdf/Qnx8QnU1tawbt2zPPjgXEJDb30Q//CHLwFQWVnBpk0/4L33/nRXP+vatStcv17E8uVLByX2O4kEIYwYda317Ck9yNGKE1idti7XA6QBaFXRaFUaYtqThq79X5A8aFBisDvtFDeVcrW+gCvGQoqbSnC6nO0/X85EdQoTIpOZoE4mPjSu0wf+2PAkliQuxGQ1c7H2Mhdq87lcf42vSvbzVcl+QgKCSY2aRJpmMpMixxMoU3Qbg9Vh6/TB3ur5sG+lxdZyRwLo+OB3P25z2r16ncerTiOVSJmpmz7wN22E6egNAERHa4iIiKShwdgpQfSmtLSEX/3qDRoaGlAqlbz00qskJCSye/cX/OEPv0cqlREWFsabb24jJ+d3WK0WLlw4yzPPfLtfvQ9viAQh+L1SUzm7S/I4U63H6XKiDoxgecLDjAtPoqalFkNLDYaWGqrb/1turuzyHOGKULQqDcmaROKD4kmJGIcqQNnnz3a6nFSYq9qHjAoobLiB1WEF3MNFCWGj3UlBnczY8EQCZAF9PmeoIoS5o2Yxd9QsrA4b14yF6GsvcaH2MseqTnGs6hRyqZyUiLEoAxU0tJg6fdjbvfyQ74hRJVeiDFASGxiOSq5EFaB0P3bb16oAlfu/ciUWh5X/1eew4/JHaJXRJISN9vrnDYU/7y3k5JXqAT+PTCbB4XCPwM+aqOVrmcl9tOgqP/8idruNuDjv36M33niNzZv/D3Fxo9Hrz/GrX73Br371G3Jyfsdbb/2WyMgoTCYTgYFBfOc73+X69SJ++tMf+2T4TiQIwS+5XC6uGAvYfTOPK8YCAOJCYnkkIYMZ2mnIpO5Nk4lh8V3aNVgaPUnj9sRR2HCDgobrQPuHe+hoz1/7Y8OTULR/uHdMLF9tn0sw25o9z69TaZnY3sbbJNMbhSyA1OhJpEZPwulyUmIq40JNPvr23kVHrB0f5OrAiFsf8B0f7p4PelWnBKAKUBIoC7yrYatvT/kGv9X/gd9e+AObZn6f8ED/2VA2VGpra/nP/9zCK6/8BKnUu/fYZDJx6dJFXnllk+cxh8Od8NPSpvHTn/4HixY9QkbGIp/EfCeRIAS/4nA6OFut56uSPMrMFQCMVyezJCGDSZHjkUgkOJxO9pwuo7iyqY9niwAiUJJCEpCAHVtQA3WOUkzSSm42lXHTVMqXN/chcUkJdmpwBbTS7Lz1vOGKMGbHzGCCOpkJkclEBIb76qUjlUhJCksgKSyB5eMew2xtRqcNx2y0ddmE6gtWm4OC8kau3DQSr43iibGP8dn1f/DOxT/y/fR/JkA6uB8nV0uMVNQ2s+iB/vVQvpaZfFd/7d9pIJPqzc1mNm3ayHe/+yKpqWlet3O5XERERHQ7J/HSS69y6dJFjhw5yLe//TTvvffBXcXWHyJBCH7B4rBytOIke0sPUNdmRIKEB7RTeSQho1MvoazGTM6uy9yoHEh3O9b9T2pHGmpEGlaHLKwOc7ABl1WO06RDJx/N7IRUFk4ajyqo72EjXwhRBKMKUNIs8X5IqT8cTifFVSbyi41cLq6nsLwJu6N9PkUu5c0X51PeXMkpwzn+39W/8szENYOWqJxOF+/szKeuycLsybphe4/vhs1m4+WX/53HHssmM7N/cwJhYWFERUWRl7ePjIxFOJ1OiooKSUkZT0VFOampaUyZksrhwweora1GpVLR0tLc9xPfJZEghHuayWomr+wIB8qO0GxvIUAawIK4eSxOeJhoZZTnPrvDya5jN/n74WIcThdzp+h4fF4SAbL+DZ9ERoVQX2fu9prZ2srVYhMnKmu4UdlE6WUDn+2pYVpyNHMm60gbG0WA3H+PWHG5XFTUtXC5uJ78YiNXS420Whye6wnaECYnRdJisXPgfAVHL1bxzIw1GFpqOFp5kriQWBbFPzQoseiL6qhrsgDQYLb6VYLYu/crzp07Q2NjI7t27QTglVf+g5SUCV61//GPf8Yvf/k67777Nna7jUcfzSIlZTy//vUvqayswOVy8eCDcxg7Nhm1Ooo//el9Vq5cydNPf2vQJ6nFPoh2/rRG259ihbuLt6aljj2lBzhWeRKb005wgIqMuHksGD2PUEXnmlw3q0y8u+sypdVmIkIUfPOxiUxPjvZprAZjC8fzDRy7ZKCq3l0HTBkoZ+YEDXMm65iQoEYq9f2wz0B/F+qb2sgvNpJ/s57LN400mq2ea9oIJZOT1ExKimRiQgShKveqKVOLlR/+5ghR4UH87LuzabA08vNTv6bZ1sK/TlvHxMiUAcf6qz+f58L1OgD+/RvpTEpU3/VrvFv+9P8zX9ViEj0I4Z5ys6mUr0ryOFd9ARcuooLUZCYsYG7srC7LOm12J38/coNdR0twulwsmBbL1xYlD8lfmzq1iifmj2H5vCRKDGaO5xs4ftnAQX0lB/WVhIcomD1Jx+zJOpJiQodkjsAb5lYbV24ayb/pHjYyGFs918KCFcyZrGNSoppJSWqiw7ufYA9VKZg1UcPRSwYu3zQyOSmS9WnfZNuZ3/L7izv495nfQ6u6uwQNUNPQysX25ADQaLbc9XMJAyMShDDsXC4X+fVX+ermfs8qovjQOJYkZDBdk+ZZkXS7oopGcnZdoaK2maiwIL6dNZEpYyKHOnQkEgmJMaEkxoSyZtE4CkobOJZv4NSVar48WcqXJ0vRqZXMnuxOFrFRQ1tGw2JzUFDW0D6PYKTEYKJjyCBIIWN6crQnIcRFB3udyBalj+boJQP7z5YzOSmSseFJfH3Ck/zfKx/x2wt/4Ecz/hXlXe4t2X+uHBcwY4KG01draLitVyMMLZEghGHjcDo4ZTjH7pI8zw7jSZHjeSQhgwnq5G4/rCw2B58evM6XJ0txuSDzgThWZ4xDGTj8v8pSiYQJCWomJKh5Zsl4Lt6o53i+gbMFNfztcDF/O1xMoi7UkyzUoYGDHoPD6eRGpckzj1BU0Yi9fS2/XCZhQkJEe0KIZExsKDIvl1/eaVxcGKM1wZwtqKXBbCEiJJB5o2ZRYa5kX9kh/pD/AevTvtXvJbQ2u5OD5ysJDpLzyIzRnL5aQ1OzSBDDZfj/XyXcd9rsbRypOMHe0kMYLQ1IJVJm6dJZnJBBfOioHttdLTGS848rVBtb0aqVfCdrIhMShn5s2htymZTpydFMT46mzWrnXEEtx/INXLpRz819Jj7aV8iEhAhmT9YxY4KWEOXdDYu5XC7KasxcLjaSX1zP1dIG2qzuiWUJkBATyuT2HkLK6AgCAwbncHuJRMKi9Dje//IaB85X8MT8MQCsSs6mstnAhdrL7Lz+JU+Me6xfz3v6WjXmVhtLH4wnKtzdA2loFkNMw0UkCGHINFpM7C87xMHyY7TaW1FIA1g0+iEWxT9MlLLnD/o2q51P9l9nz5kyJMCjs+JZtWDsoH3Y+VqQQs6cKTHMmRKDqcXKqas1HL9UxZWSBq6UNLDjy2tMSlIT2s8kYbU5KapsosF06wNUF6libqKaSYlqJiaq7zrxeGPOlBj+vL+IvHMVZM9NRCaVIpPKWJv6DG+ceosvbu4lLiSGGf0ox7H/TDkAC6fHER7s7mE1iiGmYSMShOBzFU1VfHTlHxyvPI3d5SAkIJjHxyzl4dFzCAnofUz+UnE9f/jHFWob24iNUrF22STGxfluM5qvhaoULEqPY1F6HHWNbZy4bOBYvoGL1+vv6vkiwwKZO0XHpMRIJiepiQwbnJpS3lAGypk7JYb9Z8vRF9aRPt5deTY4QMW/TP02b576b96//BEaVTQJoX1vdiurMXOtrJEpSWp0kSr3cwXJaRRDTMNGJAjBJ1psreTXXeF0tZ4Ltfm4cKFRRrE4YQGzY2Z6ylb02L7Nzp/3FXDgfCVSiYTsuYk8MT+JgAGeO34viQoPImtOIllzEmlstuJo34TmLYlEQsqYKGpru9+3MRQWpcex/2w5+86WexIEQGyw7lY5Dv0feGnW99HQezmO/Wfbew/pt5JJeEig36xiGupy33l5+ygvL+Xpp7856K+lg08TxIEDB3jttddwOp089dRTrF+/vtP1iooKXnrpJUwmEw6Hgx/96EdkZGR0up6dnc2GDRtYt26dL0MVBkFdaz362nwu1OZT0HDdU8V0XGQii0YtYJpmileTlucLa/njF1cxmiyM1oSwLnsSiTEju9ZPeHD3lVn7MtzLZ+O1ISTHhXPxRj3Vxha0apXnWlr0ZJaPXcrfrn/O7y78kf+M+WGPz9NmtXPkYhXq0ECmp9zaABkerKCithmb3eE3fxwMZrlvu92OXN79x/RQ1GPyWYJwOBxs3bqVnJwcdDoda9asITMzk+TkWzVStm/fTlZWFk8//TSFhYWsX7+evXv3eq7/13/9Fw8//LCvQhQGyOlyUmoq9ySF26ukJobGkxY9mamayUxLSvHqr1xzq40Pdhdw9FIVMqmElQ+NYdncROT93A0tDK1F6XEUljey/1wFX1vUuQbSo4mLKDdXcrr6PDlnP2JV4vJun+NYvoE2q4OlDyZ0WlkVEeJOnI3N1h73ZdxrBlru+4UX1jF9+gPo9efIyFhEbOwo/vjHHOx2GxERarZs+U/U6kj+/vdPuX69iI0bf8iPfvQjAgODuXIln7q6OjZs+MGgJBCfJQi9Xk9iYqLnLOns7Gz27NnTKUFIJBLMZvcHh8lkQqvVeq7t3r2b0aNHo1KpEO4dNoeNaw1F6Gvc5acbre7CdXKpnClRE0mLnkxa9KROReu8+Sv39NVq3v/yGk3NVpJiQlm7bBKjtSF9thOG38yJGj7YE8AhfSWrHh7bqdyIRCLh2UlPUdFcxZ6iQ2TGLOxS+dXlcrH/TDlSiYQF0zqvYrt9otrbBPGXwp2crb4wwFcFMqkEh9O9RDhdm8aTyY/3+znuptw3QEtLM7/5ze8AaGpq4u23M5BIJHz66cd88MEOXnzx+13aGI31bN/+e4qKCtmyZfO9nSAMBgMxMTGe73U6HXq9vtM9HUNHO3bsoLW1lZycHABaWlr43e9+x7vvvsu7777r1c9Tq1XIB9gF7W3L+b1mqGM1Wcz8/sz/43TFBSx295hwqCKYjKQ5zIybyjTdJIICep4g7SneBpOF//2rnsPnKwiQS/l29mRWZoxDNoy9Bn/6PYB7I95HZyfyl/2FXKtoYuGM+C7Xl45fwHtnP+J6WwGPjs7odO3KzXpKqs3MTYtl/NjOO7Dj2ocWXTKZ169TVa5ANkhlTjqeR6VU9PnzJRJJp3uqq6v52c9+zBtv/BydrvuFFRZLMHJ559cWECBj9eqVnsfq6sp56aVXqa2txWq1kpSUhEYTSmhoEEplgOe+xx/PQqsNQ6t9gNramkH5vfBZguiuxNOdf0nm5uayatUq1q5dy9mzZ9m0aRM7d+7krbfe4lvf+hbBwd7vOjUaWwYU7/1Sd+Vu/b+rn3Kk/BQaZRRTR81mavQUxoQleHY5mxpsmOh6iht0H6/L5eL4ZQN/+qoAc6uN5LhwvrNsIrFRwdTX+646ZV/86fcA7p14H5wQzV/2F/LZgSKmJER0uZ6sdNdnOnj9FOnhnY8q/ete93ke86bourwWWfu+79KKBpJjvOtRPhb3KI/FPdr3jX24873t6312uVyee5qbzXzve//M2rX/QlzcuB7b1tc3Y7c7Ol232RxYLLee69VXt/DNb36HuXMf4uTJ4+zY8QdqakyYTG20tto897W23nqe22Px5nX2xGcJIiYmhqqqW+fvGgyGTkNIAB9//DHvvPMOAOnp6VgsFoxGI+fPn+eLL77gzTffpKmpCalUSmBgIM8++6yvwhV6Ud9m5EjFcaKVUfyf2T/qtvRFfxhNFt7/4irnCmtRyKV8Y3EKi2eMHpLidoJvaNUqUsdEcvFGPWXV5i7Dg+qgCFIikygwXsdkNXsKLppbbZy4XI1Orey2IF/HEJM/ldsYSLnv7jQ3m4mO1uJyufj8852DEKH3fJYg0tLSKC4uprS0FJ1OR25uLr/85S873RMbG8vRo0d58sknKSoqwmKxEBkZyZ/+dGtG/6233kKlUonkMIy+KN6L3eVgWdIjA0oOLpeLQxcq+XBPIa0WOxMTIvh21sROK18E/7UoPY6LN+rZd7ac55Z2LW09O/4BCuqL0ddeYv6o2QAc0ldidzhZmB6HtJu5qtsnqf3FQMt932nt2vW8/PK/o9VqmTRpCrW1dX03GiQ+SxByuZwtW7bw/PPP43A4WL16NSkpKWzbto3U1FQWL17M5s2befXVV3nvvfeQSCS8/vrrw75sT+isrrWeI5Un0aqiB3RAfV1jG3/4/AoXb9QTpJDxzaUTWDB9VLcfCoJ/mpochTo0kCOXqlizsGt9rDmj09lx/i+crb7A/FGzcbpc5J0rRy6TMj8tttvn7Fj+6w97Ib766iAAS5cuY+nSZV61iY0dxfvv/7nTY9u3/77T9wsXLmbhwsVd2i5fvtLz9ZtvvtlpSKkjloHy6T6IjIyMTvsaADZu3Oj5Ojk5mQ8//LDX5/je977nk9gE73xevAeny8mypCV31Xtwulz848gNfv/3S1isDlLHRPKtxyZ66uwII4dMKiVj2ig+PXSDY/kGFqXHdbquDYkmITSOq8ZCmm0tFJe3YTC2Mi81pseSIMpAOQFyKQ1+1IMYScQCc6FHNS11HKs6TYxKywzdtH63b7XYefODs/zPJ3pkEglrl03i//vaNJEcRrCHp7l7hfvOlHe7UCVdMxWny4m+Nt9Td+nORHI7iURCeLBCVHQdJiJBCD36R/Fud+9hzJJ+l20G2HXsJldKGpg5Scd/Pj+bh6bGiiHEEU4dGkj6+GjKaswUVTR1uT5dmwrAyYrznC2oJUEbwthRYb0+Z3iIO0E4R8bhl35FJAihW4aWGk5UnWFUcAzp2rR+t69vauPLk6WoQwPZ/K1ZPjn7QLg3dfQI9rX3EG6nVWmIC4nlWmMBTqmVhQ/E9flHQ0RwIA6nC3NL98uoBd8RCULo1j9u7MaFi+y77D18evAGNruTlQ+P8Zuy3MLgmJTorsZ68or7bIc7TYtOxYWToOg65kzW9fl84X64kmmkEAlC6KKq2cApwzlGh4xiqmZKv9uXVZs5fKGSOE0w81O7X50ijFwSiYRF00dhdzg5pK/scj2oxb3TOjLeSJCi73Uy/rSSaaQRCULoYld77+Fu5x4+zivCBTy1MFlsfrtPzUuLJUAuZf/Z8i5zB+cutuJsCcEkK6fN3veHfniI/22WGylEghA6KTdXcqZaT3xoHFOjJ/e7/eXievRFdUxKVJM2NtIHEQr+IEQZwIOTtFQ3tJJffOswJEN9C5eKjUQ4ErG77Fyqu9Lnc93aLCd6EENNJAihk47ew+NjHu33iiOny8Wf9xcB8NSicWLF0n1uUfvBP7dPVu8/5/56QZK7HtPZmr6rroqjR4ePSBCCR6mpgnM1F0gMi2dK1MR+tz9x2cDNKhNzJutIiul96aIw8o2JDSVRF8q5wlrqm9qw2Bwc0lcSqgpg8eTJaJXRXKq9jNXR+wd/xyS12Cw39ESCEDx23fgK4K56Dza7k7/kXUcuk7BqwVhfhCf4GYlEwqIH4nC54MD5Cg6fr6C5zc7DU0ehCJAxXZuG1Wkjv+5qr88TplIgkUCTmKQeciJBCACUNJWhr73E2PBEJkWO73f7fWfKqG1sI/OB0Wgi/OPkL8H3Zk/SoQyUkXe+gtzD15EAGdPdhwJ17K/pa5hJKpUQqlKIHsQwEAlCACD3xpcAZN9F76G5zcbfjxSjDJTz+LwkH0Qn+KtAhYx5U2JpNFu5VtJA6tgozx8Q8SFxRAVFcqE2H5uj901wEcEKMQcxDESCELjRWMLFuiskR4xhgjq57wZ32HX0Js1tdh6fm9hj0TXh/rUw/dYxorfXXZJIJEzXpmJxWLliLOj1OcJDArHYHLRZ7T6LU+hKJAjB03u4m7mHusY2vjpVRmRYIItn9O/cXeH+EKcJIT0lmqTYMKaOi+p0LV0zFaDPM6RvbZYTvYih5NNy38K973pjMZfrrzFenUyKely/23968Dp2h5NVD49FIUpqCD3Y8GQaGk0otbXmTo8nhcWjDoxAX3sJu9OOXNr9R5JnJZPZgi5SHDA1VEQP4j6Xe929cil7zJJ+ty0xmDhysYp4bQhzp8QMdmjCCCKRSLrtnXYMM7Xa27hqLOyxvacHISaqh5RPE8SBAwdYunQpS5Ys4e233+5yvaKigueee46VK1eyfPly8vLyANDr9axYsYIVK1bwxBNP8NVXX/kyzPtWgfE6V4wFTIocT3LEmH63/3h/e0mNReNESQ3hrnkzzBQRIjbLDQefDTE5HA62bt1KTk4OOp2ONWvWkJmZSXLyrUnQ7du3k5WVxdNPP01hYSHr169n7969pKSk8MknnyCXy6murmbFihUsWrQIuVyMiA2mWyuX+t97uHSjnos36pmcpCZ1TFTfDQShB2PCEwhXhKKvuYRjwpPdnlwoKroOD5/1IPR6PYmJicTHx6NQKMjOzmbPnj2d7pFIJJjN7jFJk8mEVqsFQKlUepKBxWIRJRt84JqxkIKG60yJmsiY8MR+tXW6XHy0zz0c8NTC/q96EoTbSSVSpmnSaLa3UNBwvdt7REXX4eGzP8kNBgMxMbfGpXU6HXq9vtM9GzZsYN26dezYsYPW1lZycnI8186fP8/LL79MRUUFb7zxRp+9B7VahVw+sElSjSZ0QO2H0kBidblcvKV3J+tnH1iJJrJ/z7XvdCkl1WYWzhjNzLRRfTfg/nlvh4M/xdtTrItcszlQfoTLpis8POGBLtdDw917J1qsjiF9vSPhvR0InyWI7s6jvbMnkJuby6pVq1i7di1nz55l06ZN7Ny5E6lUyrRp08jNzaWoqIiXXnqJBQsWEBjY86lkRmPLgOLVaEKpqTEN6DmGykBjvVx/jSu1RaRFTybMEdmv57LZHfxh5yXkMgnLHoz3qu399N4ONX+Kt7dYo9EREhDMsZIzrEjI7rbMvDJQRo2xdche70h5b71p2xOfDTHFxMRQVVXl+d5gMHiGkDp8/PHHZGVlAZCeno7FYsFoNHa6Z9y4cSiVSq5du+arUO8rLpeL3Ot3P/ew53Q5dU0WHpkRT3S4KKkhDA6pRMp0TSpmWzOFDTe6vScsOFCU/B5iPksQaWlpFBcXU1paitVqJTc3l8zMzE73xMbGcvToUQCKioqwWCxERkZSWlqK3e7eMVleXs6NGzeIi4vr8jOE/suvv8qNphKmaVKJD+3fe2putbHzSDHBQXKy5/Vv3kIQ+pKu7X01U0SwAlOLDbvDOZRh3dd8NsQkl8vZsmULzz//PA6Hg9WrV5OSksK2bdtITU1l8eLFbN68mVdffZX33nsPiUTC66+/jkQi4fTp0/zud79DLpcjlUr58Y9/TGSkOHxmoFwuFzsH0HvYdfQmLRY7X1uUTHCQKKkhDK6UiLEEy1Wcr7nAU+Of6DLM1LGSydRiQx2/QZjrAAAgAElEQVTa83CzMHh8um40IyODjIyMTo9t3LjR83VycjIffvhhl3YrV65k5cqVvgztvnSx7jIlpjLStVOJC+nfWdG1ja3sPl1KVFggi2eI3pww+GRSGVM1UzhaeZIbjSWMi0jqdL3j4KAGs0UkiCEidlLfJzp6DxIkLEt6pN/t/3rgOnaHi1ULxhIwwNVigtCTWyXA9V2ueY4eFZvlhoxIEPeJ87WXKDNXMEM3jVEh/SuLUWIwceySgQRtCHNESQ3Bhyaok1HKgzhbfQGnq/NcQ7g4m3rIiQRxH3C6nOS29x6y7qL38FF7SY01i8YhFZsWBR+SS+VMjZ5Cg6WRm01lna6Js6mHnkgQ94FzNRepaK5iVkw6McHavhvc5lJxPZdu1DNFlNQQhkhPw0zibOqhJxLECOd0Ocm98RVSiZSspMX9bHurpMYaUVJDGCIT1SkEyhScq77YacPtrYJ9YohpqIgEMcKdMZynqtnAgzEPoFVp+tX2eL6BEoOZOVN0JMb4T8kBwb8FyAJIi55MXVs9peZyz+PBQXJkUoko2DeERIIYwRxOB7nFd9d7sNmd/PXAdeQyCU8+PNZHEQpC99I17cNMt22ak0gkhIcoRA9iCIkEMYKdMpyjuqWWubEziVb2b/5g35kyahvbyHxgNNERoqSGMLQmR01AIQ3gbLW+0zBTeLCCxmZrt7XehMEnEsQI5XA62FW8G5lExtLE/vUeWtps/P1IMcpAOY/PS/JNgILQC4VMwXh1MjWtdZhst44pDQ8OxO5w0dxmH8bo7h8iQYxQJ6rOUNtax7xRDxKlVPer7a5jJTS32cmem0iIUpTUEIZHbLAOgOqWWs9jtzbLiWGmoSASxAjkcDr4R/Ee5BIZSxMX9attfVMbX50qRR0ayCMzRvsoQkHom0blHha9PUGEibOph5RIECPQsapT1LXVMz9uDuqgiH61/fTgDWx2JysfHoMiQJTUEIaPVuledVfdUuN5TJxNPbREghhh7E47/7ixhwCpnEcTF/arbVmNmcMXK4nTBDM/tX/F/ARhsHUsy65pvdWDEGdTDy2RIEaYo5UnMVoaeDhuLhGB4f1q+/H+IlwuWJMxDqlUlNQQhleYIoRAmaLTENPtFV0F3xMJYgSxOWx8XryXAGkAS/rZe7hy04i+qI6JCRFMHSdKagjDTyKRoFVpqGmt9RTuixA9iCHl0wRx4MABli5dypIlS3j77be7XK+oqOC5555j5cqVLF++nLy8PAAOHz7Mk08+yfLly3nyySc9p84JvTtceYIGSyMLRs8lTOH9zmeXy8VH+90lNZ5alNzl7HBBGC5aZTQ2p50GSyNw2yS16EEMCZ8dGORwONi6dSs5OTnodDrWrFlDZmYmycm3avps376drKwsnn76aQoLC1m/fj179+5FrVazfft2dDod165dY926dRw8eNBXoY4IVoeNL4v3opApWJKwsF9tT16p5kaliVkTtYyJDfNNgIJwF7SqaMC9kikySI1cJiVEGSB6EEPEZz0IvV5PYmIi8fHxKBQKsrOz2bNnT6d7JBIJZrN7E4zJZEKrdVcanTx5Mjqdew10SkoKVqsVq1X8QvTmUMUxGq0mFo6eT6gixOt2doeTv+RdRyaV8GSGKKkh3Fs6Jqo7zUOEKGgQq5iGhM96EAaDgZiYW4fL6HQ69PrO5Xs3bNjAunXr2LFjB62treTk5HR5ni+++IJJkyahUCh6/XlqtQr5AE8602j8pyDd7bG22S3sPryfIHkgX09fRmig9wli56HrVDe08vj8MaSO1/kiVMB/31t/4E/x9jfW8dIEyAcTjZ62GrWK8ppmwiJUBPp4KfZIfm+94bME0V2tlDvHtnNzc1m1ahVr167l7NmzbNq0iZ07dyKVujs2BQUFvPnmm7z77rt9/jyjsWVA8Wo0odTUmAb0HEPlzlh3l+TRaDHxWNJi2ppctOHd62i12PnTF1cIVMh45IE4n71+f35v73X+FO/dxBpgUwFws67C01bZnhSKiuvQ+LBO2Eh/b29v2xOfDTHFxMRQVVXl+d5gMHiGkDp8/PHHZGVlAZCeno7FYsFoNAJQVVXFhg0b+PnPf05CQoKvwvR7bXYLX93cT5AsiMXxD/er7efHSzC12Fg2O8Ez+ScI95LgABUhAcHUdFtuQwwz+ZrPEkRaWhrFxcWUlpZitVrJzc0lMzOz0z2xsbGeFUpFRUVYLBYiIyNpampi/fr1/Nu//RszZszwVYgjwoGyI5htzWQmPIwqQOV1uwazhS9OlhAeouDRWSIBC/cujTKa2rZ6HE4HAOEdu6nF2dQ+57MEIZfL2bJlC88//zzLli0jKyuLlJQUtm3b5pms3rx5M3/+85954okn+Ld/+zdef/11JBIJO3bsoKSkhP/5n/9hxYoVrFixgrq6Ol+F6rda7W3sLslDKVeSGf9Qv9p+dugGVpuTFQ+NIVAhSmoI9y6tKhqny0ltWz3gLvkNiInqIeCzOQiAjIwMMjIyOj22ceNGz9fJycl8+OGHXdq9+OKLvPjii74MbUTYX3qYZnsLy8cuRSn3fiy2sq6Zg+criY1S8fBUUVJDuLd5Sm601KJTaW7bLCd6EL4mdlL7qRZbK3tKDxAsV7Fw9Px+tf14fxFOl4vVGeOQScWvgHBvu7UXwl20L1wU7Bsy4tPBT+0rPUirvZVHEjMIkgd53a6grIGzBbUkx4WTnhLtwwgFYXBole7fU0N70b5wUfJ7yIgE4YfMlmb2lh4iJCCYBXHzvG7ncrn48z53SY2viZIagp/QtPcgOlYyBSlkKAKkomDfEPAqQeTm5mK3iyP+7hU7r+2mzdHGksSFBMkDvW535lotReVNPDBeQ/Lo/lV6FYThEihTEBEY7tlNLZFIPGdTC77lVYLYuXMnmZmZbNu2DYPB4OuYhF6Yrc3suraPUEUIC+Lmet3O4XTySV4RUomE1aKkhuBntMpojJYGrA4b4J6HaGq24nR23ZArDB6vEsT27dv54IMPsNvtrF69mu9///scO3bM17EJ3dhTeoA2u4WliZkoZN5vbjt4vpKq+hYWTIslNirYhxEKwuDrmKjuODwoIliBywWmFtGL8CWv5yDi4uL44Q9/yK9//Wv0ej0vvPACy5cv59SpU76MT7iNzWHjcPlxwgJDmD9qttftLFYHnx26gSJAyhMPjfFhhILgG5rbqrrCrYODxDCTb3m1D8JqtbJr1y4++OADHA4HP/jBD1i2bBl6vZ5Nmzaxd+9eX8cpAOdrLtJsb+GJ5EdRyAK8bvfFyRIam60sn5fkOdNXEPyJ7ra9EHDr6NEGs5UE39WYvO95lSAyMzOZPXs2mzdvJj093fP4zJkzmTvX+3FwYWAOVRwHYPHY+dDmXZumZiv/OF5CqCqAx2aLkhqCf9J4lrp27IUQBwcNBa8SxF/+8pcuhfY6vPbaa4MakNA9Q0sNBQ3XSYkYS2yolpo27yo3/u3wDSxWB2syxqEM9OnGeUHwmWhlJBIkYohpiHk1B/Hpp5/S0NDg+d5oNPLOO+/4LCihqyMVJwB4qB9zD4b6FvLOVaBVK8mYPspXoQmCz8mlcqKUkZ4hJlHRdWh4vQ8iIiLC871arWbnzp0+C0rozO60c6zyFMFyFdM0qV63++TAdRxOd0kNuUzsiRT8m1YZjclmpsXWKiq6DhGvPjW6O/zH4XAMejBC9/S1+ZhtzTwY+wABXk5OF1U0cupKNWNiw5g5QePjCAXB925f6hqqDEAigQYxxORTXiWIpKQkcnJycLlcOJ1O3n33XXGIzxA6XO6enPZ2aavL5eKjfUUAfG3ROFFSQxgRbj+fWiqVEBasEJPUPuZVgnjllVfYt28fU6dOZfr06eTl5bFlyxZfxyYAta31XDEWMDY8idhg79bznS+q41ppA9PGRTEhQe3jCAVhaHQU7euo6hoRHEhjs7XbEQ5hcHi1rEWn0/HHP/6Rlhb3uc8qlfcnlwkDc7R9cnr+qAe9ut/pdPHJ/iIkElizcJwvQxOEIeUp+916ay/ETYOJNqtDrNDzEa9nLk0mE4WFhVy6dImTJ09y8uTJPtscOHCApUuXsmTJEt5+++0u1ysqKnjuuedYuXIly5cvJy8vD3CvknruuedIT09n69at/Xg5I4vD6eBo5UmU8iAe0E71qs3hC5WU1zYzPy2WOE2IjyMUhKGjDopALpXfttS1Y7OcGGbyFa/S7q5du/j5z39OU1MTWq2WkpISJk6cyF//+tce2zgcDrZu3UpOTg46nY41a9aQmZlJcnKy557t27eTlZXF008/TWFhIevXr2fv3r0EBgayceNGCgoKKCgoGPir9FMX667QaDWxIG6eV3WXLDYHnx66QYBcykpRUkMYYaQSKdHKKKpbanG5XJ6VTE3NVlFfzEe86kH87//+L3/5y19ITEzkiy++4J133mHq1N7/otXr9SQmJhIfH49CoSA7O9tzFnUHiUSC2WwG3D2Ujs14KpWKmTNnEhh4f5eFOFLRMTnt3fDS7lOlGE0WlsyMJzLM+0OEBMFf6JTRtDnaMNuaxdnUQ8CrHoRcLicqKsqztHX+/Pm89dZbvbYxGAzExMR4vtfpdOj1+k73bNiwgXXr1rFjxw5aW1vJycnpb/wearUKuVx21+0BNJrQAbUfTLUt9Vyqv0pyZBLpYyd0uX5nrI1mS3tJDQXffHwKwUrvazUNhXvpve2LP8UK/hXvQGNNjI7jfO0lrIpmEka5zzSxI/HZe3A/vbfd8SpBKBQKXC4XiYmJvP/++8TFxWE0Gntt093KgjuXW+bm5rJq1SrWrl3L2bNn2bRpEzt37kR6F+ckG40t/W5zO40mlJoa78pXDIXcG/txuVw8qJ3RJa7uYv1gdwEtbXb+aXEKLeY2WsxeFmsaAvfae9sbf4oV/CvewYg1BPeH4NWKErTO8QBUGJp88h7cL+9tb4nFq0/ijRs3Yjab+dGPfsSePXv4zW9+w3/8x3/02iYmJoaqqirP9waDoUs9p48//pisrCwA0tPTsVgsfSae+4HT5eRoxUkCZQpmaKf3eX9NQyt7z5QRHR7EovS4IYhQEIaHVtle1bW1tlNFV8E3+kwQDoeDkpISQkNDSUpK4r333uOTTz5h3rzez0JOS0ujuLiY0tJSrFYrubm5ZGZmdronNjaWo0ePAlBUVITFYiEyMnIAL2dkyK+7itHSwExduldHiv61vaTGkwvGEiAXJTWEkcuz1LWlxjMHIcpt+E6fQ0wymYzPPvuMr3/96/17YrmcLVu28Pzzz+NwOFi9ejUpKSls27aN1NRUFi9ezObNm3n11Vd57733kEgkvP76655hqMzMTMxmMzabjd27d/Puu+92WgE1kh3px96Hm1UmjuUbSNSF8uBkURhfGNnCFKEEyhRUt9SiCJChDJSLiq4+5NUcxLx58/j888957LHH+vXkGRkZZGRkdHps48aNnq+Tk5P58MMPu217vx5C1Ghp4kLdZeJDRpEQOrrXe10uF3/eVwjAmkXjkIqSGsIIJ5FI0Ko0VDUbcLqcRIQoREVXH/IqQezYsYOGhgaCgoJQKpW4XC4kEolneEgYPEcrT+F0OZk3anafNZQu3ajn8k0jqWMimZIkhuaE+4NWGU2pqZwGSyPhwQoq61qwO5yiYrEPeJUgPvnkE1/HIeCenD5ScQKFNIBZMb1PTjtdLj7aX4QEUVJDuL9obzuf+vbNcmLvz+DzKkHExYmVMUPhqrGQurZ65sTORClX9nrvsUtVlFabmTslhgSd/6zVFoSBur2qa3iwO1k0mEWC8AWvEsScOXO6He4QQ0yD67Bncrr3st5Wm4O/HriOXCZh1QJRUkO4v3ScT13dWkNEiPuPV1H22zf6PcRksVj4+9//jlwuqicOJpPVjL7mEqOCYxgT1vtZGzsP3aCuycLSB+OJDu+9pyEII43n4KCWWuI8S13FRLUveDWrExcX5/k3duxYNm7cyPHjx30d233lWOUpHC4H80Y92OvkdHObjY/2XEMVKCd7btLQBSgI94jgABUhAcHtcxCioqsv3dW0f2lpKeXl5YMdy33L5XJxpOIEcqmcB2Me6PXeXUdvYm61kT0vkZB7rN6SIAwVjTKa2rZ6QoLdIxlNogfhE/2eg3A6ndjtdl555RWfBnY/KWi4TnVrLbN0DxAc0PNhTOZWG3vPlBMZFsQjM3rfIyEII5lWFc2Npps4Zc2AKLfhK/2eg5DL5URHRyOTDaxyqnDLYS/Leu8+VYrF5uDZrEkEDLByrSD4s46VTCaHEblMKspt+IhXQ0zNzc2o1Wri4uLQ6XRYLJb7+iCfwWS2NXOu5iI6lYbkiJ5XJLVZ7ew5XUZwkJylcxKHMEJBuPd4JqpbawkPVohJah/xKkFs3ryZgIBb491yuZyXXnrJZ0HdT05UncHutPc5OZ13roLmNjuPzIwX5+8K9z2tZ6lrHeHt5Ta6O2JAGBivEoTD4eiUIBQKhefwIOHuuVwuDlecQCaRMTtmRo/32exOvjhRQmCAjMVi7kEQ0NxR1dXhdGFutQ1zVCOPVwlCLpdTWlrq+b6kpETMQQyCG003qWo2MF2TSqgipMf7jl6qosFsJWP6KLFySRCAQJmCiMDwTuU2xDDT4PNqrGLDhg184xvf8FRmzcvL46c//alPA7sfHCp3T07P62Vy2ul0sevYTeQyCUsf7H0DnSDcT7TKaK41FBGqcv+d22i2MlozzEGNMF4liEWLFrFjxw4OHz4MwPr160lMFBOlA9Fia+VMtZ7ooEjGq3sutnfqajXVxlYWTBuFOrTvw4ME4X6hUbkThFTpPm5YbJYbfF4NMdXX1zNq1CieeeYZnnnmGUaNGkV9fX2f7Q4cOMDSpUtZsmQJb7/9dpfrFRUVPPfcc6xcuZLly5eTl5fnufbb3/6WJUuWsHTpUg4ePNiPl+QfThnOYnPamD9qNlJJ9/8zuFwuco/eRCKBrDmi9yAIt+tYyeQMMANis5wveJUg/vmf/7nTpLTNZuNf/uVfem3jcDjYunUr77zzDrm5uezcuZPCwsJO92zfvp2srCw+/fRTfvWrX/GTn/wEgMLCQnJzc8nNzeWdd97hJz/5yYiaFHe5XByqOI5UImV27Mwe77twvZ7SajOzJmrRqXveQCcI9yNd+14Ii7QJEJvlfMGrBGG1WlEqbxWFU6lUWCy9d+f0ej2JiYnEx8ejUCjIzs5mz549ne6RSCSYze7sbzKZ0Gq1AOzZs4fs7GwUCgXx8fEkJiai1+v79cLuZSWmMsrNlUyNnkx4YM+luncdLQZgmdj3IAhddFR1bXY1AuJsal/wekF9fX09kZHuU8vq6upwOp293m8wGIiJifF8r9PpunzIb9iwgXXr1rFjxw5aW1vJycnxtJ02bVqntgaDodefp1arkA9wd7FGMzTnKnxSfAaAZZMW9vgzL12v41pZIzMn6ZiROqrL9aGKdbD4U7z+FCv4V7yDGas6UonkhIRmVyMSiZYWq2PQ34v79b3t4FWCeO655/jGN77BihUrcLlc/O1vf+O73/1ur22627Ry50aw3NxcVq1axdq1azl79iybNm1i586dXrW9k9HY4sUr6ZlGE0pNjWlAz+GNNnsbh26eRB0YQaxsdI8/80+fXwbgkQfiutwzVLEOFn+K159iBf+K1xexRgVFUtFkIEQ5mRpj66A+//3y3vaWWLxKEGvWrCEhIYH9+/cD8NprrzFzZs9j5wAxMTFUVVV5vjcYDJ4hpA4ff/wx77zzDgDp6elYLBaMRqNXbf3VacN5rA4rjyYs7HFyusRgQl9UR8rocMbHRwxxhILgP7TKaPLrr6IOkVLfIIaYBptXcxAmk4mDBw9SUFDAhQsX+PWvf803v/nNXtukpaVRXFxMaWkpVquV3NxcMjMzO90TGxvrOZWuqKgIi8VCZGQkmZmZ5ObmYrVaKS0tpbi4mKlTp97lS7y3HKo4jgQJc3qZnN517CYA2XPF3IMg9KZjJZMqvI02qwOLdeQsZrkXeNWDePnllxk3bhzFxcVs3LiRTz75hClTpvT+xHI5W7Zs4fnnn8fhcLB69WpSUlLYtm0bqampLF68mM2bN/Pqq6/y3nvvIZFIeP3115FIJKSkpJCVlcWyZcuQyWRs2bJlROzcLjVVUGIqIzVqEuqg7nsGBmMLJ69UE68NIW1s1BBHKAj+paOqa4CqFVDR2GxBqxAr/gaLVwni5s2bvPXWW+zZs4fHH3+cRx99lPXr1/fZLiMjw7P7usPGjRs9XycnJ/Phhx922/aFF17ghRde8CY8v3Gkvaz3Q3E9nzn9+fESXC5376GveRdBuN91FO0jsBlQ0WC2ohVLwgeNV0NMCoX7WL+AgAAaGhoICAjoNEcg9M3isHKi6izhijAmR07o9h6jycLhC5Vo1UpmThgZcy6C4EsdQ0x2uXuCVmyWG1xe9SCSkpJoaGhg+fLlfP3rXyc0NJRJkyb5OrYR5Uy1njZHG4vi5yOTdj9c9uXJEuwOF1mzE5BKRe9BEPqiDopALpXTKnHvhRDlNgaXVwnizTffBOA73/kOaWlpmEwmFixY4NPARpoj7ZPTc2O7L8xnbrWx/2wFESEK5qXGDnF0guCfpBIp0coo6lsbAJeo6DrI+n3yTF/LW4WuKsxVXG+8yaTI8UQp1d3es/d0GRabgxUPjSFA7tXInyAIgE4ZTVWzAeRWGkW5jUElPomGwJGKEwA8NKr7yek2q52vTpUSHCRnYXrXXdOCIPSs4/AgaVALDaLcxqASCcLHbA4bx6tOE6oIIS16crf3HGg/TnTxjNEEKcRxooLQHx0T1QHBrTSJHsSgEgnCx87WXKDF3sqcmJndTk7b7E6+OFlKYICMR2bGD0OEguDftEr3Xoig0DYaxBzEoBIJwsc6hpd6OjXu6KUqjCaLOE5UEO5SRw9CpmzB1GzF0UchUcF7IkH4kKG5moKG64xXJ3t+iW/ndLr4x7GbyKQSHp0leg+CcDfCFKEEyhQ4FWZcgKnFNtwhjRgiQfjQ4cqOyenuew+nr9VgMLYyPy2GyLCgoQxNEEYMiUSCVqXBJjUBLrGSaRCJBOEjNqed45WnCQ5QMVWT2uW6+zjRYvdxorNFUT5BGAitMhqnxIFE0SY2yw0ikSB8RF9zCbOtmdkxMwiQdl2ZdPFGPSUGMzMnaNFFitoxgjAQHUO4kqAWsVluEIkE4SMdk9Pze9j7kHvUXdJbHCcqCAPXUdVVEtRMo+hBDBqRIHygtrWOK8YCxoWPISa4a9G9wrJGrpU2kDo2ksQY/znSUBDuVR3nU0uDmsVS10EkEoQPHPb0HrqfnM49WgzA43OThiYgQRjhbh9iEpvlBo9IEIPM4XRwrPIUSrmSdG3XU/BKq82cL6ojWRwnKgiDJjhARUhAcHsPQgwxDRaf1nU4cOAAr732Gk6nk6eeeqrLIUM/+9nPOH7cfYhOW1sbdXV1nDp1CoBf/OIX5OXlAfDiiy+ybNkyX4Y6aC7UXabJaiJj9HwUsq4b3zzHiYq5B0EYVBplNGZrCQ3mtuEOZcTwWYJwOBxs3bqVnJwcdDoda9asITMzk+TkZM89L7/8sufr999/n/z8fAD2799Pfn4+n376KVarlWeffZYFCxYQEhLiq3AHzeH2U+O6G16qNrZw4rKB0ZoQpo4Tx4kKwmDSqqK50XSTJnsjLpdLnMg4CHw2xKTX60lMTCQ+Ph6FQkF2djZ79uzp8f7c3Fwef/xxAAoLC5k1axZyuRyVSsXEiRM5cOCAr0IdNPVtRi7XXWNMWAJxIV3PdOg4TnTZ3ATxyysIg6xjHsIhN9FqsQ9zNCODz3oQBoOBmJgYz/c6nQ69Xt/tveXl5ZSVlTFnzhwAJk6cyH//93/zne98h9bWVo4fP96p59EdtVqFXN79SW3e0mgGtqJo38X9uHCxdEJGl+eqb2rj0IUqYqOCWfbQOGSygeXmgcY61PwpXn+KFfwrXl/GmtwWD9fdE9VSRcCg/Kz7/b31WYJwuVxdHuvpr+bc3FyWLl2KTOb+gH/ooYe4cOEC//RP/0RkZCTTp0/3XOuJ0dgyoHg1mlBqakx33d7pcrK78DBBskDGqyZ0ea4/7yvE7nCyZNZo6uubhzXWoeZP8fpTrOBf8fo61iCbewhaGtTMjVIjQQMcH7lf3tveEovPhphiYmKoqqryfG8wGNBqu+4JANi1axfZ2dmdHnvhhRf47LPPyMnJAdznYt/L8uuu0mBpZGZMOoEyRadrzW029p0tJzxEwXxxnKgg+ITm9t3UYrPcoPBZgkhLS6O4uJjS0lKsViu5ublkZmZ2ue/69es0NTWRnp7ueczhcGA0GgG4cuUKV69eZf78+b4KdVAc6mVyes/pMixWB0tnJYjjRAXBRwJlClTSECRBzTSIvRCDwmdDTHK5nC1btvD888/jcDhYvXo1KSkpbNu2jdTUVBYvXgy4h5eWLVvWafjJbrfzzDPPABASEsIvfvEL5PJ796S1Bksjl+qukBAaR0Lo6E7XLFYHu0+VERwkJ2O6OE5UEHwpKiiKFudNjM0DG3IW3Hz6qZuRkUFGRkanxzZu3Njp++9973td2gUGBrJr1y5fhjaojlWewulyMq+buksHzldgbrXxxPwklIH3bpIThJFAq4qmtOUm1S21wx3KiCDGOwbI6XJypOIECmkAM3XTO12zO5x8fqIERYBUHCcqCENgdJgOAKO1fpgjGRlEghigq/WF1LUZmambjlLe+dCfoxfbjxOdFieOExWEIRAb4l4IY3Y0DHMkI4NIEAPUMTl95/CS0+li1/ESZFIJSx8UvQdBGAodVV1bJY3DHMnIIBLEADRZTehrLxEXEktSWOckcOZaDYb6FuamiuNEBWGoRCsjwSXBEWDGZncOdzh+TySIATheebp9cvrBTquw3MeJ3kSCOBBIEIaSXCpH4QpBGuxImjAAABMPSURBVNRMo6jqOmAiQdwll8vF4YrjBEjlPKhL73TtUnE9Nw0mZkzUEiOOExWEIRUsjUASYKW6sWm4Q/F7IkHcpYKGImpa63hAOw1VQOcksOuoKOktCMMlQq4GoLSpepgj8X8iQdyljlPj5t2xc7qwvJErJQ2kjhHHiQrCcIhWukvpV5lFghgokSDugtnazLnqC8SotIwLT+p0zdN7mCt6D4IwHDqWuta21Q1zJP5PJIi7cKLqNHaXg/l3TE6X1Zg5V1hLcpw4TlQQhkt8uPuYgQab2Cw3UCJB9JN7cvoEcomMB2NmdLrWcZzosrmJ4kAgQRgmCepoXE4JzS6xWW6gRILop6LGYqpaqpmuTSNEEex5vLqhlRP51YzWBDNNHCcqCMMmOEgBlmCsUlO359II3hMJop+OtE9O31nW+/PjJThdLpbNEb0HQRhOEokEuT0Ul9SG2Taww7nudyJB9EOLrYUz1efRKKNIiRjnebzRbOGQvhJNRBCzJnV/KJIgCEMniDAAqprFSqaBEAmiH04YzmJz2pk/ananXsKXJ0uxO5xkzU5EJhVvqSAMt1BZ+16IRsMwR+LffHpAwYEDB3jttddwOp089dRTrF+/vtP1n/3sZxw/7i5219bWRl1dHadOnQLgjTfeIC8vD6fTyfz583nllVeGdejG5XJxuPw4UomU2bG3JqdbOo4TDVYwPy1m2OITBOGWSEUkVUC52Cw3ID5LEA6Hg61bt5KTk4NOp2PNmjVkZmaSnJzsuefll1/2fP3++++Tn58PwJkzZzhz5gx/+9vfAHj66ac5ceIEs2d3PZBnqBQ3lVLRXMV0TRphilsb4PacKafN6mD5/CQC5LJhi08QhFu0qmjyrVDdUjPcofg1n42H6PV6EhMTiY+PR6FQkJ2dzZ49e3q8Pzc3l8cffxxwTzJZrVZsNpvnv9HR0b4K1StH2st6P3RbWW+LzcFXJ0tRBcpZOD1uuEITBOEO2hA1LoeMOovYCzEQPutBGAwGYmJuDbnodDr0en2395aXl1NWVsacOXMASE9PZ/bs2Tz00EO4XC6effZZxo0b123bDmq1CvkA/4LXaLovjdFia+V0jR5NcBQPTUhHKnHn1b8dLMLcauPrj4wnYbR6QD+7v3qK9V7lT/H6U6zgX/EOVayJcRG4SoMxyYxERQd7/j/bX/f7e+uzBNHd+uOe5hByc3NZunQpMpn7A/7mzZsUFRWRl5cHwNq1azl58iSzZs3q8ecZjQM7pFyjCaWmxtTttYPlx7DYLcxJWEhdrXvZnN3h5JO9BSgCpMybrO2xrS/0Fuu9yJ/i9adYwb/iHcpYJQ4nzjYVzuAmCsvKUQf1v7LB/fLe9pZYfDbEFBMTQ1VVled7g8GAVtv9EtBdu3aRnZ3t+f6rr75i2rRpBAcHExwczMMPP8y5c+d8FWqfjlS4J6fnxM70PHbskoH6JgsLpo0iVKUYttgEQegqLFiBq829kdUg5iHums8SRFpaGsXFxZSWlmK1WsnNzSUzM7PLfdevX6epqYn09FtnKowaNYqTJ09it9ux2f7/9u49JqpzXQP4M8xFkJsXEKylslEUNyC6uxXwUqIgFwfUCFbb2JzaEM2pEW81qTY1UaNtPbUW29TYplVbs1NjTEubqXY3Ugu2Baq4HT3qwSqIKDOAg3IT5rbOH4NTKYurjGtWeX5/zWXNmgci63V931rfa8Fvv/3W4xCTq1Q2VqGy8TYiR0Zg2BB/AO3tRItuQumhQOr0ZyTJRURd8/NWQ2h1LMNf01IncRr5ctkQk0qlwtatW5GdnQ2bzYbMzEyEh4cjNzcXUVFRSExMBOAYXpo/f36H4aeUlBQUFRUhIyMDCoUCs2fPFi0uT8LDZb0fnZwuLauFwdSCWdGj2U6UyA0pPTzgpRgGG4DaBywQ/eXS+yASEhKQkJDQ4bW1a9d2eL5mzZpOn1Mqldi+fbsro/VKm82Ms4bzGDbEH38fORFAezvRIkc70bQ4nj0QuSt/1XCYwEtdHwdv++3GOeMFtNraED96mvMqiMsV9bhpaMSzEwMxeqR3D3sgIqkMH+oDwaKGoZkFor9YILrxy51iKKDAjKf+uHpK92sFAEAbHypJJiLqnWHeQ2Bv9YaptR42u03qOLLEAtGF203VKG+oxKSREzDC03GPw/U7jnaikWwnSuT2/H00EFqHwg477rbyhrn+cOkchJyJTU4724nGsZ0okbvzf+RS121F/yNxGteaPmYK/mviiwO+XxYIEWabBSWGUvhpfBE1chIARzvR89fqMO4pP0x8hu1EidzdMJ8hsJmC8XSoGX6+fV9lQa1WwmKRx9BU+Mi/uWS/LBAi/lN7EQ+sDzB77BwoPRz/sE6wnSiRrPh5ayC0eePvQiqy/tH3+6gGy53U3eEchIgztx0L8z3sGld77wGKL9dgTKA3YsZLu2ggEfXOMB/HCgf3m9okTiJfLBB/YmiuwfX75YgYHo4AL0dv6ZMlf7QT9eDZA5Es+HsPAQDcazZLnES+WCD+5GHP6RntZw/3m9pQeKEaAf6emM52okSyMUSjhKdGiftNLBD9xQLxCIvdiiLDWfiovRETGAkA+PfZh+1En2E7USKZ8fcZgvvNHGLqLx7xHqGvvYRmSwtiRz8LlYfK0U609Db8vDWYNXm01PGIqI/8vTVobLHAarNLHUWWWCAecaZ9eGlm+70P+e3tRFOmhbCdKJEMPZyobmyxSJxEnlgg2hmaalFW/zvCh4UhaGigo53o2fZ2olPZTpRIjpwT1bySqV94H0S7/Bs/A/hjcvqMvhqNLRakzxgLryH8NRHJkX/7GcQ7/yrt8xyihwKwd26M6Zbio0djeVL4gO+XRz4ANrsNP5b/iqEqL0wNjIbVZsfJ4pvQqDyQ9M8QqeMRUT/FjA/A+Wu1MFv6PgehUnnAapXH3EXAMC+X7JcFAsDFusu439qAOU/Pglqpxs8Xq3G3oQ2Jzz4NP7YTJZKtMQHeeOOlf/a8oQjeSe3iAlFQUICdO3fCbrdjyZIlWLlyZYf3d+3aheJix13Lra2tuHv3Ls6ePYuioiK89dZbzu1u3LiBvXv3IikpySU5f37k3ge7wHaiRESACwuEzWbD9u3bcfDgQQQFBSErKwtz587F+PHjndts2bLF+fiLL77A5cuXAQBxcXHIy8sDANy7dw/JycmYOXOmS3I2mptwxVSGiSPD8JRPMM79Xy2q77ZgZnQwRvqznSgRDV4uu4pJr9dj7NixCAkJgUajgVarxalTp7rcXqfTIT09vdPr33//PWbPng0vL9eMsak91JgyKhovTF4IQRDwXVEFFADmc0lvIhrkXHYGYTQaERwc7HweFBQEvV4vuu3t27dRVVWFuLi4Tu/pdDqsWLGix+8bPnwoVP26V8EXm0f/NwDgP2U1KK9uRHz0aEyOCO7hc9IKDJRXwyI55ZVTVkBeeeWUFZBXXldkdVmBEITO14d1tUy2TqdDSkoKlMqOB/iamhqUlZVh1qxZPX5ffX1L/4K2Cwz0xb9OXgUAJP1jjFtPTslp8gyQV145ZQXklVdOWQF55X2crN0VFpcNMQUHB8NgMDifG41GjBolvtjdd999B61W2+n1EydOYN68eVCr1a6K6VRWWY8rN+sRGTocfxvt5/LvIyJydy4rENHR0aioqMCtW7dgNpuh0+kwd+7cTtvduHEDDQ0NmDp1aqf3dDqdaOFwhWOnygAA8+NDn8j3ERG5O5cNMalUKmzduhXZ2dmw2WzIzMxEeHg4cnNzERUVhcTERACOIjB//vxOw09VVVWorq7G9OnTXRXR6XZdM4ouGRD2lB8i2E6UiAgAoBDEJgtk6HHGCj/59jJ+/V8D1iyOxtQJgQOYyjXkNDYKyCuvnLIC8sorp6yAvPLKbg5CLhpbzCi+bERIkC9iwtlOlIjooUG/1IZa5YGp4QHITJzAdqJERI8Y9GcQnhoVVi+ORvR4nj0QET1q0BcIIiISxwJBRESiWCCIiEgUCwQREYligSAiIlEsEEREJIoFgoiIRLFAEBGRqL/MWkxERDSweAZBRESiWCCIiEgUCwQREYligSAiIlEsEEREJIoFgoiIRLFAEBGRKBaIdu+//z4yMjKwcOFCvPLKKzAajVJH6tY777yD1NRUZGRkYPXq1WhoaJA6UpdOnDgBrVaLiIgIXLx4Ueo4XSooKEBKSgrmzZuHjz/+WOo43dq8eTPi4+ORnp4udZQeVVdX46WXXkJaWhq0Wi0OHz4sdaQutbW1ISsrCwsWLIBWq8W+ffukjtQjm82GRYsWYdWqVQO/c4EEQRCExsZG5+PDhw8Lb775poRpelZYWChYLBZBEARh9+7dwu7duyVO1LXff/9duH79urB8+XJBr9dLHUeU1WoVEhMThcrKSqGtrU3IyMgQrl27JnWsLpWUlAiXLl0StFqt1FF6ZDQahUuXLgmC4Pg7S05Odtvfrd1uF5qamgRBEASz2SxkZWUJ58+flzhV9z777DNhw4YNwsqVKwd83zyDaOfj4+N8/ODBAyjcvD/1rFmzoFI5WopPmTIFBoNB4kRdGzduHMLCwqSO0S29Xo+xY8ciJCQEGo0GWq0Wp06dkjpWl6ZNmwZ/f3+pY/TKqFGjEBkZCcDxdxYWFua2Z+gKhQLe3t4AAKvVCqvV6tbHAoPBgNOnTyMrK8sl+1e5ZK8ytXfvXnz99dfw9fXF559/LnWcXjt+/DjS0tKkjiFrRqMRwcHBzudBQUHQ6/USJvprqqqqwpUrVxATEyN1lC7ZbDYsXrwYlZWVePHFF906665du7Bp0yY0Nze7ZP+DqkC8/PLLqKur6/T6unXrkJSUhPXr12P9+vU4cOAAjhw5gpycHAlS/qGnvACwf/9+KJVKLFiw4EnH66A3Wd2ZILIkmTv/z1GOmpubkZOTgy1btnQ4Y3c3SqUSeXl5aGhowOrVq1FWVoYJEyZIHauTH3/8ESNGjEBUVBSKi4td8h2DqkAcOnSoV9ulp6dj1apVkheInvJ+9dVXOH36NA4dOiT5way3v1t3FRwc3GGYzmg0YtSoURIm+muxWCzIyclBRkYGkpOTpY7TK35+foiNjUVhYaFbFojS0lLk5+ejoKAAbW1taGpqwmuvvYZ33313wL6DcxDtKioqnI/z8/Pdfsy8oKAAn3zyCfbv3w8vLy+p48hedHQ0KioqcOvWLZjNZuh0OsydO1fqWH8JgiDgjTfeQFhYGFasWCF1nG6ZTCbnFYGtra345Zdf3PZYsHHjRhQUFCA/Px/vvfce4uLiBrQ4AIPsDKI7e/bsQXl5ORQKBcaMGYNt27ZJHalbO3bsgNlsdv7BxcTEYPv27RKnEvfDDz9gx44dMJlMWLVqFSZNmoRPP/1U6lgdqFQqbN26FdnZ2bDZbMjMzER4eLjUsbq0YcMGlJSUoL6+Hs899xzWrFmDJUuWSB1L1Llz55CXl4cJEyZg4cKFABz5ExISJE7WWU1NDV5//XXYbDYIgoDU1FTMmTNH6liSYT8IIiISxSEmIiISxQJBRESiWCCIiEgUCwQREYligSAiIlEsEES9MHHixMdezsBut+OFF17ocEPeN998g0WLFiE1NRVpaWlYv3497ty5A5PJhOeffx5Wq/VxoxP1G++DIHpCTp48ifDwcOeaT8eOHcPBgwfx0UcfITQ0FABQXFyMuro6TJ48GTExMcjLy0NmZqaEqWkw4xkEUR/p9XosXboUGRkZWLp0aYdF/Y4cOYLk5GRkZmZi3759iI2Ndb539OjRDv0bPvzwQ2zevNlZHAAgNjYWkydPBuBY8uXYsWOu/4GIusACQdQHZrMZOTk5WLt2Lb799lusW7cOOTk5MJvNuHr1Kg4cOIAvv/wSx48fR2Njo/NzFosF58+fdx787969C4PB0O1KoZGRkbh69SpaWlpc/nMRiWGBIOqD8vJyqNVqzJgxAwAQHx8PtVqN8vJylJSUICEhASNGjACADkND9fX1UKvV8PT0BCC+euyfqVQq+Pj4oLa21gU/CVHPWCCI+kAQBNGVcxUKRZfvAYCnpyfa2tqczwMCAnrVc8JsNjuLCtGTxgJB1AdhYWEwm80oKioCABQVFcFqtSI0NBSxsbH46aefYDKZADiWY3/Iz88PAQEBqKqqcr726quv4u2330ZlZaXztcLCQly4cAEAUFdXB6VSyWXHSTK8iomoDzQaDfbt24edO3eipaUFQ4cORW5uLjQaDSIiIpCdnY1ly5YhICAAM2bMgK+vr/OzSUlJOHPmDJYtWwYAWLZsGTw9PZGTk4PW1lZ4eHggIiICmzZtAgCcOXMG8+bNk7zXBw1eXM2VaAA1NTU5u6V98MEHuHnzpnON/lu3bmHjxo04evRorw76y5cvx7Zt2zBu3DiXZibqCs8giAbQnj17UFpaCovFgpCQkA49OkJCQrBixQrU1NQgKCio2/2YTCYsXbqUxYEkxTMIIiISxUlqIiISxQJBRESiWCCIiEgUCwQREYligSAiIlH/D7dN/N7WxcIcAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot CV误差曲线\n",
    "test_means = grid_svc.cv_results_[ 'mean_test_score' ]\n",
    "test_stds = grid_svc.cv_results_[ 'std_test_score' ]\n",
    "train_means = grid_svc.cv_results_[ 'mean_train_score' ]\n",
    "train_stds = grid_svc.cv_results_[ 'std_train_score' ]\n",
    "\n",
    "# plot results\n",
    "n_Cs = len(tuned_parameters_svc['C'])\n",
    "number_penaltys = len(tuned_parameters_svc['penalty'])\n",
    "test_scores = np.array(test_means).reshape(n_Cs,number_penaltys)\n",
    "train_scores = np.array(train_means).reshape(n_Cs,number_penaltys)\n",
    "test_stds = np.array(test_stds).reshape(n_Cs,number_penaltys)\n",
    "train_stds = np.array(train_stds).reshape(n_Cs,number_penaltys)\n",
    "x_axis = np.log10(tuned_parameters_svc['C'])\n",
    "\n",
    "for i, value in enumerate(tuned_parameters_svc['penalty']):\n",
    "    #pyplot.plot(log(Cs), test_scores[i], label= 'penalty:'   + str(value))\n",
    "    plt.errorbar(x_axis, test_scores[:,i] ,label = tuned_parameters_svc['penalty'][i] +' Test')\n",
    "    plt.errorbar(x_axis, train_scores[:,i] ,label = tuned_parameters_svc['penalty'][i] +' Train')\n",
    "\n",
    "plt.legend()\n",
    "plt.xlabel( 'log(C)' )                                                                                                      \n",
    "plt.ylabel( 'accuracy' )\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAEGCAYAAAB/+QKOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAAIABJREFUeJzt3Xl8U1X+//HXzdaNRUqbVlnqAHVgpGJ/4oCySRGwlIJYGBbBBZgySAVURASGGRlBRB0GFxhQKQLjqICCEhSVSusGLjBWv4gKghSRUGiRltKs9/dHbLASSkpzk4Z+no8HD5rmJnn3QvPJOeeecxRVVVWEEEKI39CFOoAQQoj6SQqEEEIIn6RACCGE8EkKhBBCCJ+kQAghhPDJEOoAgVJcXFanxzdrFk1paUWA0mgrnLJCeOUNp6wQXnnDKSuEV966ZI2Pb3zO+6QF8QuDQR/qCH4Lp6wQXnnDKSuEV95wygrhlVerrFIghBBC+CQFQgghhE9SIIQQQvgkBUIIIYRPUiCEEEL4JAVCCCGET1IghBBC+HTRTJQToorLBStXGtm5s/bXhkdGQmVlpM/7FAVSU10MHuwkLq7hrZJfWQk7duj54AM9f/iDmyFDnJq+3kcf6dmzR8fYsQ5NX0ecmxQIcVHZt0/h7ruj+OyzukwcMp7znldeMfLXv6qkpbkYNsxBv35OoqLq8FL1mKrC7t06tm3Tk59vYPt2PZWVCgCRkSq9e5dzySXavLbLBXffHUlRkY6hQx00aaLN64iaSYEQFwW3G557zsi8eRGcPq0wZIiD6dNtRETU7nmaN2/E8ePlPu+z2+GddwysXWvk7bcNvP22gcaNVTIzHQwb5uS661zowrzT9sgRhfx8Pdu2GSgo0FNcfOYH6tDBRa9eLsrK4D//MbF+vZFx47T5dJ+fr6eoyPPaR48qNGnS8Fps9YEUCBH2fvhBYerUSD780EDz5m6efrqSzMwL6/6Ij4eoqHO/GU2Y4GDCBAfffKNj7VoD69cbefFFEy++aKJlSzdZWQ6GDnXy+9+7L/THCapTp2D79jMF4euvz7S84uPdDB3q4IYbnPTq5SIhwXNejh5VePllI6tWGRk71oGiBD7XqlVnWnFHj+po184V+BcR5yUFQoQtVYXVq4387W8RnDqlkJ7u4LHHbJjN2n/a/P3v3cyebWfmTDsff6xn7VoDb7xhZPHiCBYvjuCqqzxdUEOGOIOSx19uN3z5pY5t2wzk5+v55BM9drvnHT4qSqV3bye9ejm54QYXHTq4fb75m80q6elO3njDyOef6+jcObDF0GpV2LLlzFvT0aMaVCDhFykQIiwdPqxwzz2RvPeegSZNVJ555jRDhzo1+TRbE50OunVz0a2bi0cesfH2254uqLw8PX/9ayR//7tKr16eYpGe7iQ6Orj5AA4dUsjP9xSEggI9JSVnuo1SUlzeFsIf/+gi0vf4/FnGjHHwxhtG1qwx0rmzLaB5X3rJiMul0LOnk4ICgxSIEJICIcKKqsIrrxiYNSuSkycV0tKcLFpUyaWXhv5TelQUDB7sZPBgJ8eOKWzcWFUsDOTlGYiJUcnIcDJsmIPu3V3oNVostLwcPvxQ720l7N175oUuu8zNyJGebqMePVwXfDVWz54uWrd2s2GDkblzbQEbRHa7Pa3C6GiViRPtUiBCTAqECBtHjypMmxbBW28ZiYlReeKJSkaP1qYPvK7i4lTGjXMwbpyDvXsV1q0zsm6dkVde8fxJTHSTleVk6FAHV15Zty4apxP+9z8d+fkGtm3T8/nnepxOz0mJjlbp1+9Mt1G7dr67jWpLp4PRox3Mnx/B+vVG7rwzMIPVBQV6Dh7UMXKkgzZtPOfl6NEwH/kPY1IgRFh4/XUD06dHUFKio3t3J//6VyWtW4e+1eCPdu1UZsyw88ADdnbs8IxXvP66kWeeMfHMMyb+8AcXN9/spHnz2v08p0/Dzp3w7ruNOHnS866v06lcfbXb2210zTUuTCYtfioYOdLBo4+aWL3ayB13BKZQr1njGZweM8ZOfPyZQXERGlIgRL1WUgIzZkSyYYORqCiV+fMrGTvWEZaXkyoKdO3qomtXF/Pm2Xj3XQNr1xp4910D8+fX8nrcX2ndWmXwYAc33OCiRw+nZnMTfishwdM6efNNI198oePqq+vWEjp6VGHzZgMdOri45hpPSycmRpUCEUJSIES99dZbeu67L5LiYh2dO7t4+unTtGkTHq2G84mMhIEDnQwc6KSkBD74wIDdXrvn0OshLS2KJk1Ohayb7bbbHLz5ppHVq41cfXXdBqtfftmI06lw221nWiNmsxSIUNK0QBQUFDBv3jzcbjfDhg0jOzu72v2HDx/mgQceoKysDJfLxbRp0+jVq1e1+zMyMsjJyWHcuHFaRhX1yM8/w+zZkbz8shGTSeWvf7Vx1112zQZ1Qy02FgYNuvB5G8XFAQ5UCzfc4KJlSzevvmrkoYdsNGp0Yc+jqp7upchIlaysM+MZZrObTz/V43Jx0f7712eaNdRdLhdz587lueeew2KxsGnTJvbu3VvtmKVLl5Kens6GDRtYtGgRDz30ULX7H3nkEXr06KFVRFEPvfeenl69Ynj5ZSOdOrl4990K7r774i0O4U6vh1tvdXDqlMJrr517iZLz+fBDPfv36xg0qHoXmdms4nYrlJRIKyIUNCsQhYWFJCUl0apVK0wmExkZGWzdurXaMYqiUF7uWdagrKwMs9nsve/dd9+lZcuWJCcnaxVR1CPl5TBtWgTDh0dz9KjC9Ok2Nm+uoH378JiR3JCNHOlAp1NZvfrCC0TVY8eMqX41VNUkQ+lmCg3NCoTVaiUxMdF7OyEhAavVWu2YnJwc3njjDXr27El2djazZ88GoKKigmeffZacnByt4ol65KOP9NxwQwyrVpno0MHFli0VTJtmx3jh7zciiC67TKVvXxf/+5+eL7+s/VvKsWMKFouB3//eM1nv16RAhJZmYxCqevZgovKbkTSLxcKQIUMYO3Ysu3btYvr06WzatImnnnqK22+/nZiYGL9fr1mzaAyGuvVDxMc3rtPjgymcsoLvvBUVMHMmLF7sua7+wQfhb3/TExHh/7+7Fi6GcxtsOTmwZQusWxdDWtq5j/OVddUqz0KIf/mLHrO5+v1t2nj+rqyMJj4+kIn9Ux/Orb+0yKpZgUhMTOTIkSPe21artVoXEsC6det47rnnAEhNTcVms1FaWsoXX3zBli1bePzxxzl58iQ6nY6IiAhGjx59ztcrLa2oU974+MYUF5fV6TmCJZyygu+8n32m4+67o9i3T0fbtm6eeuo0nTu7OXkyRCF/cTGc21C45hq49NIYVq9WmD69HF+f7XxlVVX497+jiYjQkZ5eftaAe1SUHohm714bxcW1vMyrjurLufVHXbLWVFg062JKSUnhwIEDFBUVYbfbsVgspP3mo8Wll17Kxx9/DMC+ffuw2WzExsby4osvkpeXR15eHrfffjsTJkyosTiI8GGzwcMPmxg4MJrvv1eYMMHO1q2nAr7gmwgugwFGjXJQXq7w+uv+f+7cvt2zFMjAgU5iY8++X7qYQkuzAmEwGJgzZw7jx49nwIABpKenk5yczOLFi72D1TNmzOCVV15h0KBB3HvvvSxYsOCsbihx8Sgs1NGvXzRPPhlBy5YqGzac5h//sIVkATsReLfe6kBRVFat8n/qdtWy3r8dnK5SVSCKi+V9IRQU1ddgQRiqa1OwoTQnQ+GSSxoza5aNRYtMOJ0Kt99u529/u/Br5rUUbue2vuUdOTKKrVsNvPfeqbPWmPpt1tJSuOqqRrRsqfLRR74n+9nt0LJlY7p3d/Lqq6e1jl9NfTu3NQm7LiYhAPbs0dG1Kzz2WARms8rLL1fw2GP1sziIuqtqCVStqVSTtWuN2GwKY8bYzzkT3GSC2Fi3dDGFiBQIoZmvvtLRt280O3fC8OEO8vNP0bu37Ax2Mevb10lCgpt164xU1HDdSNVmTyaTyvDhNc8i9yy3IW9VoSBnXWjm4YcjsNkUVq+Gp56qpGnTUCcSWjMaPYPVP/+s8MYb5x6s/uQTPd98o2fAgPOvYhsfr3LihIItsPsSCT9IgRCa+PBDPXl5Bnr0cCIXoDUso0Z5uplqmll9Zlnv8+8jUTVQfeyYdDMFmxQIEXCq6mk9AMyaJR/7GpqkJJUbbnDyyScGvvnm7LeYEydg40YDv/udm27dzt/lKJe6ho4UCBFwW7Z4djXLyHDw//6fzG9oiGoarF6/3khlpcLo0f7t6xEfX7WznBSIYJMCIQLK5YL58yPQ6VQefDC4M19F/dG/v5O4ODevvGKksvLM91XVM/fBYFAZPty/bUrPtCDk7SrY5IyLgFq/3sCePXqGD3dyxRXSemioTCbPKq+lpZ6F+Krs3Knj66/1pKc7vW/85yNdTKEjBUIEjM0GCxdGYDKp3H+/jD00dLfeevZg9bmW9a6JFIjQkQIhAmb1aiMHD+q4804HLVteFBP0RR20aaPSo4eTjz4ysHevwsmTsGGDkdat3fTs6f98GCkQoSMFQgREeTn8858mYmJUpkyRsQfhcWaw2sSLL0JFhf+D01ViY1X0epksFwqa7kktGo7ly00cO6Zj2jQbcXHSehAe6elOmjd38/LLBj74APR6lZEj/e9eAs9eIfHxqrQgQkBKsqizkhJ45hkTzZu7mThRWg/ijIgIGD7cyfHjOgoLPVc3JSTU/gOE2azKiq4hIAVC1NmTT0ZQVqYwdaqdxuGzAZcIktGjz3xoqM3g9K+ZzSoVFQq/bGEvgkS6mESdHD6s8PzzRlq0cHP77Rf2yy8ubu3aqQwY4ODwYSM33HBhizWazWcmyzVqJF2YwSItCFEnTzxhwmZTmD7dRmRkqNOI+mrlykp27QL9BW4bHx8vk+VCQc62uGD79im8+KKRK65wMWxYzUs2C1EXsrNcaGhaIAoKCujfvz99+/Zl+fLlZ91/+PBhxowZw80330xmZib5+fkAFBYWMnjwYAYPHsygQYN45513tIwpLtCCBRG4XAozZtgxSGel0JDMhQgNzX6tXS4Xc+fOJTc3l4SEBIYOHUpaWhrt2rXzHrN06VLS09MZNWoUe/fuJTs7m7y8PJKTk1m/fj0Gg4GjR48yePBgevfujUHeheqNL77QsXGjkdRUFxkZ0noQ2pICERqatSAKCwtJSkqiVatWmEwmMjIy2Lp1a7VjFEWh/JfLEsrKyjCbzQBERUV5i4HNZkM5136EImTmzTuznLf88wit/XqQWgSPZh/JrVYriYmJ3tsJCQkUFhZWOyYnJ4dx48axZs0aTp8+TW5urve+L774gpkzZ3L48GEWLlx43tZDs2bRGAwXOAL2i5o2765vQpn1vfdg2za48UbIyor26zFybrUTTnkvNGuE5/MIJ06YiI83BTBRzRrCua2JZgVCVc++FO23LQGLxcKQIUMYO3Ysu3btYvr06WzatAmdTkenTp2wWCzs27ePBx54gJ49exJR9b/Eh9LSGjbA9UN8fGOKi8vq9BzBEsqsqgr33x8N6Ln//lMUF59/xVY5t9oJp7x1yaqqEBXViEOH3BQX1+133V8N5dzWVFg062JKTEzkyJEj3ttWq9XbhVRl3bp1pKenA5CamorNZqO0tLTaMW3btiUqKopvv/1Wq6iiFt5808Dnn+sZONBBaqos5y2CQ1E8l7rKVUzBpVmBSElJ4cCBAxQVFWG327FYLKSlpVU75tJLL+Xjjz8GYN++fdhsNmJjYykqKsLp9Ax8/vjjj+zfv58WLVpoFVX4yeWCRx4xyWZAIiSqlttwy+eSoNGsi8lgMDBnzhzGjx+Py+UiKyuL5ORkFi9eTMeOHenTpw8zZsxg9uzZrFy5EkVRWLBgAYqi8Pnnn/Pss89iMBjQ6XT8/e9/JzY2Vquowk9r1xr45hs9t95qJzlZfktFcJnNbhwOPSdOgLwdBIei+hosCEN17StsKP2NF8pmg+uvj+HoUYXt20/RooX//23k3GonnPLWNev990fwwgsmCgpO0b699h9QGsq5DckYhLi4rFplpKhIxx13OGpVHIQIFJkLEXxSIMR5lZfDokUmGjVSmTpVxh5EaEiBCD4pEOK8qjYDmjjRTvPm0noQoSEFIvikQIgayWZAor44M5ta3raCRc60qNFTT3k2A5oyxU6jRqFOIxoyaUEEnxQIcU4//XRmM6A77pDNgERondkTQgpEsEiBEOf0xBMmKisVpk2zy2ZAIuQiI6FpU5lNHUxSIIRP33/v2QyobVs3w4dL60HUD2azWwpEEEmBED4tXBiB06kwY4ZNNgMS9YbZrHL8uIJDPrMEhRQIcZavvtLx6qtGUlJcZGbKZkCi/oiPV1FVhePHpRURDFIgxFkWLDizGZBO/oeIekSuZAou+fUX1ezYoefttw1cd52T3r1doY4jRDVSIIJLCoTwUlWYP9+zW5dsJSrqI9l6NLikQAiv997T8/HHBvr1c/LHP8py3qL+OdOCkLeuYJCzLABwu2HevAgUReXBB22hjiOETzJZLrikQAgA3njDwJdf6hkyxMmVV0rrQdRPMgYRXJoWiIKCAvr370/fvn1Zvnz5WfcfPnyYMWPGcPPNN5OZmUl+fj4AH374IbfccguZmZnccsst3m1JhTacTs+VSwaDygMPSOtB1F9xcSo6ncymDhbNpkC5XC7mzp1Lbm4uCQkJDB06lLS0NNq1a+c9ZunSpaSnpzNq1Cj27t1LdnY2eXl5NGvWjKVLl5KQkMC3337LuHHjeP/997WK2uC99JKRfft03H67nd/9TpbzFvWXXg/Nm6syBhEkmp3lwsJCkpKSaNWqFSaTiYyMDLZu3VrtGEVRKC8vB6CsrAyz2QzAH/7wBxISEgBITk7Gbrdjt8tS01qorITHHzcRFaVy331yjkX9Fx+vShdTkGjWgrBarSQmJnpvJyQkUFhYWO2YnJwcxo0bx5o1azh9+jS5ublnPc+WLVvo0KEDJpOpxtdr1iwag0Ffp8w17c1a3wQq6z//CYcPw/TpkJKi3XreDfHcBks45Q1E1pYtYfduiIlpTHR0AELVoKGd29/SrECo6tldFcpvLqy3WCwMGTKEsWPHsmvXLqZPn86mTZvQ/TJ997vvvuPxxx9nxYoV53290tKKOuVtKBuU/1pZGcybF0OTJgrjxpVTXByAcD40xHMbLOGUN1BZL7kkEjCye3c5SUnadYk2lHNbU2HRrIspMTGRI0eOeG9brVZvF1KVdevWkZ6eDkBqaio2m43S0lIAjhw5Qk5ODo8++iitW7fWKmaDtnSpiZISHZMm2WnWLNRphPCPTJYLHs0KREpKCgcOHKCoqAi73Y7FYiEtLa3aMZdeeqn3CqV9+/Zhs9mIjY3l5MmTZGdnc++993LNNddoFbFBO3ZMYelSE3Fxbv78Zxl7EOFDJssFj2ZdTAaDgTlz5jB+/HhcLhdZWVkkJyezePFiOnbsSJ8+fZgxYwazZ89m5cqVKIrCggULUBSFNWvWcPDgQZYsWcKSJUsAWLFiBc2bN9cqboOzeLGJU6cUZs2yyVaiIqzIXIjgUVRfgwVhqK59hQ2lvxHgxx8VunaNwWxW+eijU0REBDCcDw3p3AZbOOUNVNYPPtBzyy3R3HefjQce0K7121DObUjGIET99fjjJmw2hfvvt2leHIQINGlBBI8UiAZm716F//7XyBVXuBg2TDYDEuGnapBaZlNrTwpEA/PooxG43QozZtjR123aiBAh0bQpmEwqxcXy9qU1OcMNSGGhjo0bjaSmusjIkNaDCE+KIrOpg0UKRAMyf75nwGHmTNkMSIQ3s9lTIC6OS2zqLykQDcTHH+vJyzPQo4eTXr1kK1ER3sxmFZtN4eTJUCe5uEmBaABUFR5++EzrQYhwd2Y2tbyFacmvs2uxWHA6pc86XL3zjp5PP9WTnu7gmmtkMyAR/mRnueDwq0Bs2rSJtLQ0Fi9ejNVq1TqTCCC32zP24NlKVJbUEBcHmQsRHH4ViKVLl/Lf//4Xp9NJVlYWkydPZvv27VpnEwHw2msGdu/WM2yYk/btpfUgLg5SIILD7w68Fi1acN999/Hkk09SWFjIxIkTyczM5LPPPtMyn6gDh8Mz78FoVJk+XcYexMVDVnQNDr8W67Pb7WzevJn//ve/uFwupk6dyoABAygsLGT69Onk5eVpnVNcgP/8x8iBAzrGjbPTurVcDyguHlUtCJkspy2/CkRaWhpdunRhxowZpKamer/fuXNnrrvuOs3CiQtXUQFPPGEiOlrlnntk7EFcXGSQOjj8KhCvvvrqWZv9VJk3b15AA4nAeP55E1arjqlTbd5PW0JcLGJiICZGZlNrza/22YYNGzhx4oT3dmlpKc8995xmoUTd/PwzPPWUiUsuUZk0SVoP4uJUNZtaaMfveRCXXHKJ93azZs3YtGmTZqFE3SxZYuLECYWcHDtNm4Y6jRDaMJvdHDum4JKFATTjV4HwtaeQy49/lYKCAvr370/fvn1Zvnz5WfcfPnyYMWPGcPPNN5OZmUl+fj7gaaGMGTOG1NRU5s6d609E8YujRxWWLTNhNrsZP15aD+LiZTaruN0Kx49LK0IrfhWIyy+/nNzcXFRVxe12s2LFClq3bl3jY1wuF3PnzuW5557DYrGwadMm9u7dW+2YpUuXkp6ezoYNG1i0aBEPPfQQABEREUyZMoXp06df4I/VcP3rXyYqKhTuvddOdHSo0wihHZkLoT2/CsSsWbN47733uOqqq7j66qvJz89nzpw5NT6msLCQpKQkWrVqhclkIiMjg61bt1Y7RlEUysvLASgrK/MOhEdHR9O5c2ciZLuzWjl4UOGFF4y0bu1m9GhHqOMIoSkpENrz6yqmhIQEVq1aRUVFBeB5Az8fq9VKYmJitecoLCysdkxOTg7jxo1jzZo1nD59mtzc3Npkr6ZZs2gMhrrtgFPT3qz1ja+s99/vmRw3b55Cixb162cJ93Nbn4VT3kBmbdvW83dlZTTx8QF72moa6rmt4leBAM8n/P3792OznZmRe+21157zeF/jFspvNiGwWCwMGTKEsWPHsmvXLqZPn86mTZvQ6Wo/+aW0tKLWj/m1cN+g/JtvdKxeHU2HDm5uvLGC4uIQhfMh3M9tfRZOeQOdNSpKD0Szd6+N4uLAj7c1lHNbU2Hxq0Bs3ryZRx99lJMnT2I2mzl48CDt27fntddeO+djEhMTOXLkiPe21Wo9ay7FunXrvJfLpqamYrPZKC0tpXnz5v7EEr+yYIEJt1vhwQdtspWoaBDOzKaWLiat+PVR/d///jevvvoqSUlJbNmyheeee46rrrqqxsekpKRw4MABioqKsNvtWCwW0tLSqh1z6aWX8vHHHwOwb98+bDYbsbGxF/ijNFy7dumwWIx07uyif3+55k80DFIgtOdXC8JgMNC8eXPvpa3dunXjqaeeOu9j5syZw/jx43G5XGRlZZGcnMzixYvp2LEjffr0YcaMGcyePZuVK1eiKAoLFizwdkOlpaVRXl6Ow+Hg3XffZcWKFbRr166OP+7Fad48z2D+rFmylahoOOLiZJBaa34VCJPJhKqqJCUlsXr1alq0aEFpael5H9erVy969epV7XtTpkzxft2uXTteeukln4+VBQD98/77egoKDNxwg5Nu3aT1IBoOoxFiY91SIDTkV4GYMmUK5eXlTJs2jb///e+UlZXxt7/9Tets4jxUtXrrQYiGxmxWOXJEVnTVynkLhMvl4uDBg1x33XU0btyYlStXBiGW8MebbxrYuVNPZqaDTp1kMyDR8MTHq+zZo2CzgUybCrzzll69Xs/GjRuDkUXUgssFjzxiQqdTmTFDltQQDZMMVGvLr7bZ9ddfz1tvvaV1FlEL69YZ+OYbPSNGOEhOltaDaJhkNrW2/BqDWLNmDSdOnCAyMpKoqChUVUVRFO8lqiK47HZ47LEITCaVadOk9SAaLtl6VFt+FYj169drnUPUwvLlcPCgjgkT7LRsKZsBiYbrTAtCB8hVfIHmV4Fo0aKF1jmEn06dgocf9uymNWWKtB5EwyZjENryq0B07dr1rHWUAOliCoHnnjNhtcK999q9E4WEaKhkb2pt1bqLyWaz8cYbb2Aw+L3OnwiQigpYutRIs2Zw113SehBCBqm15ddVTC1atPD+adOmDVOmTGHHjh1aZxO/8dJLRkpKdEyaBE2ahDqNEKEXG6ui16u/jEGIQLugs1pUVMSPP/4Y6CyiBi4XLF1qIiJCJScn1GmEqB90Ok83k7QgtFHrMQi3243T6WTWrFmaBhPVWSwGfvhBx2232UlIMNWr/R6ECCWzWWXvXh2qiixWGWC1HoMwGAzExcWhl00HgkZV4emnTSiK+svYgynUkYSoN8xmlcJChVOnoFGjUKe5uPjVxXTq1CmaNWtGixYtSEhIwGaz8d1332mdTfzio4/0/O9/egYMcNKmjVy5JMSvyWQ57fhVIGbMmIHRaPTeNhgMPPDAA5qFEtU9/bSnxTBpkly5JMRvVZ8sJwLJrzPqcrmqFQiTyeTdPEhoa/duHVu3Guja1UnnzrLmkhC/JZe6asevAmEwGCgqKvLePnjwoIxBBMmSJdJ6EKImMptaO34NUufk5DBy5Ejv7nD5+fk8/PDD531cQUEB8+bNw+12M2zYMLKzs6vdf/jwYR544AHKyspwuVxMmzbN+xrLli1j3bp16HQ6Zs+eTY8ePWr7s4W9w4cVXn3VwBVXuOjbV1psQvgis6m141eB6N27N2vWrOHDDz8EIDs7m6SkpBof43K5mDt3Lrm5uSQkJDB06FDS0tKq7Su9dOlS0tPTGTVqFHv37iU7O5u8vDz27t2LxWLBYrFgtVq588472bJlS4NrtSxbZsLpVLjrLjs66V4VwicZpNaOXwWipKSEyy67jFtvvRUAh8NBSUkJsbGx53xMYWEhSUlJtGrVCoCMjAy2bt1arUAoikJ5eTkAZWVlmM1mALZu3UpGRgYmk4lWrVqRlJREYWEhqampF/ZThqGff4bVq40kJLjJynKGOo4Q9ZYMUmvHrwIxYcIEVq1a5b3tcDj4y1/+wiuvvHLOx1itVhITE723ExLOu/IGAAAYs0lEQVQSKCwsrHZMTk4O48aNY82aNZw+fZrc3FzvYzt16lTtsVartcaMzZpFYzDUrYURH9+4To8PpBUroLwcZs9WaNny7Fz1Kas/wilvOGWF8MqrRda4OIiKgpISQ8Cfv6GfW78KhN1uJyoqyns7Ojoam81W42NU9ezr9X+7IqzFYmHIkCGMHTuWXbt2MX36dDZt2uTXY3+rtLSixvvPJz6+McXFZXV6jkCx2WDRohgaNVLIyio/a9Z0fcrqj3DKG05ZIbzyapk1Pj6Gw4ehuPhUAJ+zYZzbmgqL322ykpIS79fHjx/H7a75ksvExESOHDnivW21Wr1dSFXWrVtHeno6AKmpqdhsNkpLS/167MVs/XoDVquOMWMcNG0a6jRC1H9ms0pxscJ53pZELflVIMaMGcPIkSNZsmQJzzzzDKNGjeL222+v8TEpKSkcOHCAoqIi7HY7FouFtLS0asdceuml3j0l9u3bh81mIzY2lrS0NCwWC3a7naKiIg4cOMBVV111gT9ieHG7PZe2GgwqEybIpa1C+MNsduN0KpSWykB1IPnVxTR06FBat27Ntm3bAJg3bx6dO3eu+YkNBubMmcP48eNxuVxkZWWRnJzM4sWL6dixI3369GHGjBnMnj2blStXoigKCxYsQFEUkpOTSU9PZ8CAAej1eubMmdNgrmB65x09336r509/cnDZZbKshhD++PVkuebN5fcmUBTVV4f/b5SVlbF8+XL27NlDZWWldzzg1wPXoVbXvsL60t84aFAU27cb2LbtFH/4g+/2cn3J6q9wyhtOWSG88mqZ9fHHTSxcGMHatRX06hWYOUMN5dzWeQxi5syZ6PV6Dhw4wPDhw9Hr9Q2myyeYPvtMx/btBvr0cZ6zOAghziazqbXhV4H44YcfmDp1KpGRkQwcOJBly5bx1VdfaZ2twXnmGc+yGjk5MvYgRG3IbGpt+FUgTCbPG5fRaOTEiRMYjcZqVxmJutu3T2HzZgNXX+3i+utlWQ0hauPMbGqZLBdIfg1SX3755Zw4cYLMzEyGDx9O48aN6dChg9bZGpQlS0yoqkJOjl12xRKilmRFV234VSAef/xxAO68805SUlIoKyujZ8+emgZrSI4eVXjlFSNJSW4yMmRZDSFqS7qYtOFXgfi1813eKmrv+eeN2GwKEyfaaCBX8woRUJGR0LSpKoPUASYddiFWXg65uSaaN3czYoQj1HGECFtms1taEAEmBSLEXnzRyIkTCmPHOoiODnUaIcKX2axy/LgOh3zOChgpECHkcMC//20iKkpl7Fj5Xy1EXVQNVB87Jq2IQJECEUKvv27g0CEdI0c6ZHkAIepIrmQKPCkQIaKqnolxOp3KX/4iE+OEqKuqK5lkoDpwpECESH6+nq++0pOZ6eTyy6X1IERdydajgScFIkSqltWYNElaD0IEgmw9GnhyJkPgyy915Ocb6N7dydVXy6J8QgSCTJYLPCkQISCL8gkReDJIHXhSIIKsqEhh40YDHTq46N1bFuUTIlDi4lR0OlUKRADVeqmN2igoKGDevHm43W6GDRtGdnZ2tfvnz5/Pjh07AKisrOT48eN89tlnADz22GPk5+cDcNdddzFgwAAtowbNsmUmXC6FSZNkUT4hAkmvh+bNVRmDCCDNCoTL5WLu3Lnk5uaSkJDA0KFDSUtLo127dt5jZs6c6f169erV7N69G4Bt27axe/duNmzYgN1uZ/To0fTs2ZNGjRppFTcoSkthzRojl13mZsgQWZRPiEAzm1V++EEKRKBodiYLCwtJSkqiVatWmEwmMjIy2Lp16zmPt1gsDBw4EIC9e/dy7bXXYjAYiI6Opn379hQUFGgVNWhWrjRRUaEwYYIdozHUaYS4+JjNKuXlChUVoU5ycdCsBWG1WklMTPTeTkhIoLCw0OexP/74I4cOHaJr164AtG/fnqeffpo777yT06dPs2PHjmotD1+aNYvGYKjbUqg17c1aV5WV8Pzz0LQp3HNPJI0bR9bp+bTMqoVwyhtOWSG88mqdtXVrz99ud2Pi4+v+fA393GpWIFT17Mlfyjk63S0WC/3790f/y1rX3bt358svv2TEiBHExsZy9dVXe+87l9LSun1k0HqD8lWrjBw9GsnkyTYqK+1UVl74c4XTZuoQXnnDKSuEV95gZG3c2ARE8PXXp2jUqG6XkDeUc1tTYdGsiykxMbHatqRWqxWz2ezz2M2bN5ORkVHtexMnTmTjxo3k5uYCnl3twpXL5dkxzmRS+fOfZVE+IbQik+UCS7OzmJKSwoEDBygqKsJut2OxWEhLSzvruO+//56TJ0+Smprq/Z7L5aK0tBSAPXv28M0339CtWzetomrurbcMfP+9jmHDHCQkyLIaQmhF5kIElmZdTAaDgTlz5jB+/HhcLhdZWVkkJyezePFiOnbsSJ8+fQBP99KAAQOqdT85nU5uvfVWABo1asRjjz2GwaDpFbmaUVV4+mnPxLiJE6X1IISWpEAElqbvur169aJXr17VvjdlypRqt+++++6zHhcREcHmzZu1jBY0O3bo+fxzPTfd5OCKK2RZDSG0JAUisKSjTmNVy2rcdZe0HoTQWtWKrrLkd2BIgdDQN9/o2LLFQOfOLrp0kWU1hNBa06ZgMsls6kCRs6ihpUs9s+FkWQ0hgkNRPN1M0sUUGFIgNHLkiMLatUbatnVz002yrIYQwVJVIHxMxRK1JAVCI88+a8ThUJg40c555vgJIQLIbHZjtyucPBnqJOFPCoQGyso86y7Fxbn5059kcFqIYDqzcZC8vdWVnEENrF5tpKxM4c9/dhBZtyWXhBC1JDvLBY4UiACz2z17PkRHq9xxh+wYJ0SwyVyIwJECEWCvvWbgp590jB7toFmzUKcRouGRAhE4UiACSFU9i/Lp9SoTJkjrQYhQqJosJwWi7qRABFBenp6vv9YzeLCTVq3kGjshQkFWdA0cOYMBVLUo36RJ0noQIlRkkDpwpEAEyK5dOj780ECvXk5SUmRRPiFCJSYGGjWS2dSBIAUiQKoW5cvJkdaDEKEmy20EhhSIANi/X2HTJgMdO7ro2VMW5RMi1MxmN8ePK7jk17FOpEAEwL//bcLtVsjJkUX5hKgP4uNV3G6F48flF7IuNN0wqKCggHnz5uF2uxk2bBjZ2dnV7p8/fz47duwAoLKykuPHj/PZZ58BsHDhQvLz83G73XTr1o1Zs2ZV23Wuvjh2TOGll4y0auVm0CBZlE+I+uDXcyGqvha1p1mBcLlczJ07l9zcXBISEhg6dChpaWm0a9fOe8zMmTO9X69evZrdu3cDsHPnTnbu3Mnrr78OwKhRo/jkk0/o0qWLVnEv2IoVRk6fVvjLX2yE6a6oQlx0ZLJcYGjWxVRYWEhSUhKtWrXCZDKRkZHB1q1bz3m8xWJh4MCBACiKgt1ux+FweP+Oi4vTKuoFq6jwFIhLLlEZOVIW5ROivpACERiafea1Wq0kJiZ6byckJFBYWOjz2B9//JFDhw7RtWtXAFJTU+nSpQvdu3dHVVVGjx5N27Zta3y9Zs2iMRjqtq52fHzjWh3/zDNQUgKzZ8Pvfle7x9ZVbbOGWjjlDaesEF55g5U1Odnzd0VFFPHxF/48Df3calYgVB+7dZxrDMFisdC/f3/0v2yc8MMPP7Bv3z7y8/MBGDt2LJ9++inXXnvtOV+vtLSiTnnj4xtTXFzm9/FOJyxcGENEhMLIkacoLg5eP2dts4ZaOOUNp6wQXnmDmTUiQgfEsH+/neJi2wU9R0M5tzUVFs26mBITEzly5Ij3ttVqxWw2+zx28+bNZGRkeG+/8847dOrUiZiYGGJiYujRowf/+9//tIp6QSwWAwcP6hg+3OGduSmEqB+kiykwNCsQKSkpHDhwgKKiIux2OxaLhbS0tLOO+/777zl58iSpqane71122WV8+umnOJ1OHA4Hn3766Xm7mIJJVT3LaiiKyl13ycQ4IeqbuDgpEIGgWReTwWBgzpw5jB8/HpfLRVZWFsnJySxevJiOHTvSp08fwNO9NGDAgGrdT/3792f79u1kZmaiKAo9evTwWVxC5cMP9XzxhZ6MDAdt2kjrQYj6xmiE5s3dUiDqSFF9DRaEobr2FdamD2/EiCjy8gy8+eYprrkm+OsuhVPfKIRX3nDKCuGVN9hZe/WK5qefdHz7bfkFPb6hnNuQjEFcrP7v/3Tk5Rno2tUZkuIghPBPXJzKiRMKtgsboxZIgai1JUtkUT4hwkHVQHVxsXQzXSgpELXw448Kr71m4IorXNx4o6wCJkR9Jlcy1Z0UiFpYtsyE06kwaZIdnZw5Ieo12Xq07uRtzk8//wyrVxtJSHBzyy2yKJ8Q9Z1sPVp3cub89MILJk6dUsjOdhAREeo0QojzkS6mupMC4QebDZYvN9Kokcrtt8vgtBDhQApE3UmB8MO6dUaOHtVx220OmjQJdRohhD+kQNSdFIjzcLthyRIjBoNKdra0HoQIF82aqRgMqoxB1IGcufN4+209332nJyvLyWWXXRSTzoVoEHQ6z9ajMg/iwkmBOI9nnvFMjJNF+YQIP1UF4uJYUCj4pEDU4NNPdezYYeDGG5106CDLaggRbsxmlYoKhVOnQp0kPEmBqEFV62HSJGk9CBGOZLJc3Wi23He427dP4c03DaSmurj+ellWQ4hwVHUl06ZNRtq1q10vQNOm8PPP4fEW2bMnNGoU+OcNj58+BJYsMaGqnmU1zrFTqhCinmvZ0lMgHn74Qme3RgUujIZSU2HLlsA/rxQIH6xWhVdeMZKU5CYjQ5bVECJcZWU5ADh9uvaPbdQokvLyygAn0kbfvpGaPK+mBaKgoIB58+bhdrsZNmwY2dnZ1e6fP38+O3bsAKCyspLjx4/z2WefsX37dh555BHvcd9//z2LFi3ixhtv1DKu1/PPG7HZFCZOtKHXB+UlhRAaiImB225zXNBj4+MjKS6+sMcGmydr4J9XswLhcrmYO3cuubm5JCQkMHToUNLS0mjXrp33mJkzZ3q/Xr16Nbt37waga9eubNy4EYATJ07Qr18/unXrplXUasrLITfXRPPmbkaMCI//HEIIoQXNrmIqLCwkKSmJVq1aYTKZyMjIYOvWrec83mKxMHDgwLO+v2XLFnr06EFUVHD6Av/zHyM//6wwdqyD6OigvKQQQtRLmhUIq9VKYmKi93ZCQgJWq9XnsT/++COHDh2ia9euZ913rsKhBYfDs+dDVJTK2LHSehBCNGyadTGpPqYuKue4HMhisdC/f3/0v+nwP3r0KN9++y3du3c/7+s1axaNwVC3AYP33mvMoUMwaRK0b6/BNWMBVNNG4/VROOUNp6wQXnnDKSuEV14tsmpWIBITEzly5Ij3ttVqxWw2+zx28+bNzJkz56zvv/nmm/Tt2xej0Xje1ystrbjwsEBcXGMeecSFTqfj9ttPUVxcf+fmx8c3pri4LNQx/BZOecMpK4RX3nDKCuGVty5ZayosmnUxpaSkcODAAYqKirDb7VgsFtLS0s467vvvv+fkyZOkpqaedZ/FYiEjI0OriNW88w783//pycx0cvnl9bc4CCFEsGjWgjAYDMyZM4fx48fjcrnIysoiOTmZxYsX07FjR/r06QN4isCAAQPO6n46dOgQP/30E3/84x+1iljNY495/pZlNYQQwkNRfQ0WhKG6NAULC3XceGMM3bs7efXVC5hRE2Th1PSF8MobTlkhvPKGU1YIr7xh18UUTpYs8SzKl5MjrQchhKjS4AvEsWMKGzcaSEmB3r1lUT4hhKjS4AtEZKRKerqTJ59EFuUTQohfafCL9TVqBCtWVBIfb9RkLRMhhAhXDb4FIYQQwjcpEEIIIXySAiGEEMInKRBCCCF8kgIhhBDCJykQQgghfJICIYQQwicpEEIIIXy6aBbrE0IIEVjSghBCCOGTFAghhBA+SYEQQgjhkxQIIYQQPkmBEEII4ZMUCCGEED5JgRBCCOGTFIhf/Otf/yIzM5PBgwczduxYrFZrqCPV6NFHH+Wmm24iMzOTSZMmcfLkyVBHOqc333yTjIwM2rdvz5dffhnqOOdUUFBA//796du3L8uXLw91nBo9+OCDXHfddQwcODDUUc7rp59+YsyYMaSnp5ORkcELL7wQ6kjnZLPZGDp0KIMGDSIjI4Mnn3wy1JHOy+VycfPNNzNhwoTAP7kqVFVV1bKyMu/XL7zwgvrXv/41hGnO7/3331cdDoeqqqq6cOFCdeHChSFOdG579+5V9+3bp44ePVotLCwMdRyfnE6n2qdPH/XgwYOqzWZTMzMz1e+++y7Usc7pk08+Ub/66is1IyMj1FHOy2q1ql999ZWqqp7fs379+tXbc+t2u9Xy8nJVVVXVbrerQ4cOVXft2hXiVDVbsWKFeu+996rZ2dkBf25pQfyiUaNG3q9Pnz6NUs83qO7evTsGg2fH2KuvvpojR46EONG5tW3bljZt2oQ6Ro0KCwtJSkqiVatWmEwmMjIy2Lp1a6hjndO1115L06ZNQx3DL2azmSuvvBLw/J61adOm3rbQFUUhJiYGAKfTidPprNfvBUeOHGHbtm0MHTpUk+dv8HtS/9qiRYvYsGEDjRs3ZtWqVaGO47f169eTnp4e6hhhzWq1kpiY6L2dkJBAYWFhCBNdnA4dOsTXX39Np06dQh3lnFwuF7fccgsHDx5k1KhR9Trr/Pnzuf/++zl16pQmz9+gCsQdd9zBsWPHzvr+1KlTufHGG7nnnnu45557WLZsGWvWrGHy5MkhSHnG+fICLF26FL1ez6BBg4Idrxp/stZnqo8lyerzJ8dwdOrUKSZPnszMmTOrtdjrG71ez8aNGzl58iSTJk3i22+/5Yorrgh1rLO89957xMbG0rFjR3bs2KHJazSoArFy5Uq/jhs4cCATJkwIeYE4X97XXnuNbdu2sXLlypC/mfl7buurxMTEat10VqsVs9kcwkQXF4fDweTJk8nMzKRfv36hjuOXJk2a0KVLF95///16WSB27txJXl4eBQUF2Gw2ysvLmTZtGo8//njAXkPGIH5x4MAB79d5eXn1vs+8oKCAZ599lqVLlxIVFRXqOGEvJSWFAwcOUFRUhN1ux2KxkJaWFupYFwVVVZk1axZt2rThzjvvDHWcGpWUlHivCKysrOSjjz6qt+8F9913HwUFBeTl5fHPf/6Trl27BrQ4QANrQdTkiSeeYP/+/SiKQosWLXjooYdCHalG//jHP7Db7d5fuE6dOjF37twQp/LtnXfe4R//+AclJSVMmDCBDh068Pzzz4c6VjUGg4E5c+Ywfvx4XC4XWVlZJCcnhzrWOd1777188sknlJaW0rNnT+6++26GDRsW6lg+ff7552zcuJErrriCwYMHA578vXr1CnGysx09epQZM2bgcrlQVZWbbrqJ3r17hzpWyMh+EEIIIXySLiYhhBA+SYEQQgjhkxQIIYQQPkmBEEII4ZMUCCGEED5JgRDCD7///e/rvJyB2+1m5MiR1Sbkvf7669x8883cdNNNpKenc88993D48GFKSkr405/+hNPprGt0IS6YzIMQIkjeeustkpOTvWs+rV27ltzcXJYsWcLll18OwI4dOzh27BhXXXUVnTp1YuPGjWRlZYUwtWjIpAUhRC0VFhYyfPhwMjMzGT58eLVF/dasWUO/fv3IysriySefpEuXLt77Xn755Wr7Nzz99NM8+OCD3uIA0KVLF6666irAs+TL2rVrtf+BhDgHKRBC1ILdbmfy5MlMmTKFN954g6lTpzJ58mTsdjt79uxh2bJlvPTSS6xfv56ysjLv4xwOB7t27fK++R8/fpwjR47UuFLolVdeyZ49e6ioqND85xLCFykQQtTC/v37MRqNXH/99QBcd911GI1G9u/fzyeffEKvXr2IjY0FqNY1VFpaitFoJDIyEvC9euxvGQwGGjVqRHFxsQY/iRDnJwVCiFpQVdXnyrmKopzzPoDIyEhsNpv3dlxcnF97Ttjtdm9RESLYpEAIUQtt2rTBbrezfft2ALZv347T6eTyyy+nS5cu5OfnU1JSAniWY6/SpEkT4uLiOHTokPd7d911FwsWLODgwYPe773//vt88cUXABw7dgy9Xi/LjouQkauYhKgFk8nEk08+ybx586ioqCA6OprFixdjMplo374948ePZ8SIEcTFxXH99dfTuHFj72NvvPFGPvjgA0aMGAHAiBEjiIyMZPLkyVRWVqLT6Wjfvj33338/AB988AF9+/YN+V4fouGS1VyFCKDy8nLvbmlPPfUUP/zwg3eN/qKiIu677z5efvllv970R48ezUMPPUTbtm01zSzEuUgLQogAeuKJJ9i5cycOh4NWrVpV26OjVatW3HnnnRw9epSEhIQan6ekpIThw4dLcRAhJS0IIYQQPskgtRBCCJ+kQAghhPBJCoQQQgifpEAIIYTwSQqEEEIIn/4/Q8s80l9HwEMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x_axis, test_scores[:,:], 'b-')\n",
    "plt.xlabel( 'log(C)' )                                                                                                      \n",
    "plt.ylabel( 'accuracy' )\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "随着C值变化，训练模型和测试模型的得分变化图。可以看出线性SVM 的训练结果的准确率是要优于 logistic 回归的。但是logsitic 回归速度是要快于 linearSVC 的"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 8 核化SVM "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 8.1 模型训练及最优值寻找"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.svm import SVC\n",
    "# 定义优化参数字典\n",
    "tuned_parameters_ksvc ={'C':[0.001,0.005,0.01,0.05,0.1,0.5,1,5,10,20,30,100], 'gamma': [100,50,10,5,1,0.5,0.3,0.1,0.05,0.03,0.01,0.001,0.0001]}\n",
    "ksvc =SVC(tol=1e-6,kernel='rbf',class_weight=\"balanced\", random_state=20)\n",
    "grid_ksvc=GridSearchCV(ksvc,tuned_parameters_ksvc)\n",
    "# 训练数据\n",
    "grid_ksvc.fit(x_train,y_train)\n",
    "ksvc_predict_test =grid_ksvc.predict(x_test)\n",
    "ksvc_predict_train =grid_ksvc.predict(x_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 8.2 结果评分及图像绘制"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "best params for kernal svm:  {'C': 100, 'gamma': 0.001}\n",
      "best score for kernal svm:  0.8452768729641694\n",
      "confusion matrix:\n",
      "[[43 10]\n",
      " [19 82]]\n",
      "regression report:\n",
      "             precision    recall  f1-score   support\n",
      "\n",
      "          1    0.69355   0.81132   0.74783        53\n",
      "          0    0.89130   0.81188   0.84974       101\n",
      "\n",
      "avg / total    0.82325   0.81169   0.81467       154\n",
      "\n",
      "accuracy score for train data: 0.85342\n",
      "accuracy score for test data: 0.81169\n"
     ]
    }
   ],
   "source": [
    "print(\"best params for kernal svm: \",grid_ksvc.best_params_)\n",
    "print(\"best score for kernal svm: \",grid_ksvc.best_score_)\n",
    "print(\"confusion matrix:\")\n",
    "print(metrics.confusion_matrix(y_test, ksvc_predict_test, labels=[1, 0]) )\n",
    "print(\"regression report:\")\n",
    "print(metrics.classification_report(y_test, ksvc_predict_test, labels=[1,0], digits=5))\n",
    "print(\"accuracy score for train data: {0:.5f}\".format(metrics.accuracy_score(y_train, ksvc_predict_train)))\n",
    "print(\"accuracy score for test data: {0:.5f}\".format(metrics.accuracy_score(y_test, ksvc_predict_test)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "def fit_grid_point_RBF(C, gamma, x_train, y_train, x_val, y_val):\n",
    "    \n",
    "    # 在训练集是那个利用SVC训练\n",
    "    SVC3 =  SVC( C = C, kernel='rbf', class_weight=\"balanced\",gamma = gamma)\n",
    "    SVC3 = SVC3.fit(x_train, y_train)\n",
    "    \n",
    "    # 在校验集上返回accuracy\n",
    "    accuracy = SVC3.score(x_val, y_val)\n",
    "    \n",
    "    return accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#需要调优的参数\n",
    "C_s = [0.1,0.5,1,5,10]# logspace(a,b,N)把10的a次方到10的b次方区间分成N份 \n",
    "gamma_s = [0.03]  \n",
    "\n",
    "accuracy_s = []\n",
    "for i, oneC in enumerate(C_s):\n",
    "    for j, gamma in enumerate(gamma_s):\n",
    "        tmp = fit_grid_point_RBF(oneC, gamma, x_train, y_train, x_test, y_test)\n",
    "        accuracy_s.append(tmp)\n",
    "        \n",
    "accuracy_s1 =np.array(accuracy_s).reshape(len(C_s),len(gamma_s))\n",
    "x_axis = np.log10(C_s)\n",
    "for j, gamma in enumerate(gamma_s):\n",
    "    plt.plot(x_axis, np.array(accuracy_s1[:,j]), label = ' Test - log(gamma)' + str(np.log10(gamma)))\n",
    "\n",
    "plt.legend()\n",
    "plt.xlabel( 'log(C)' )                                                                                                      \n",
    "plt.ylabel( 'accuracy' )\n",
    "plt.savefig('RBF_SVM_Otto.png' )\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
